Genetic Brain Tumor Markers

ABSTRACT

The invention relates to method of genetic analysis for the prediction of treatment sensitivity and survival prognosis of patients with brain tumors, especially oligodendroglial tumors. The invention provides a method for producing a classification scheme for oligodendroglial tumors comprising the steps of a) providing a plurality of reference samples, said reference samples comprising cell samples from a plurality of reference subjects suffering from oligodendroglial tumors; b) providing reference profiles by establishing a gene expression profile for each of said reference samples individually; c) clustering said individual reference profiles according to similarity; and d) assigning an oligodendroglial tumor class to each cluster.

The invention relates to the field of diagnosis of tumors, especially brain tumors, more especially oligodendroglial tumors, more particular to the prediction of susceptibility to treatment for patients with brain tumor.

Diffuse gliomas are the most common primary central nervous system tumors in adults (Legler, J. M. et al., (1999) J. Natl. Cancer Inst. 91: 1382-1390; Macdonald, D. R. (2003) Semin. Oncol. 30: 72-76) and it is estimated that approximately 18,000 new patients per annum are diagnosed with a primary brain tumor in the USA (CBTRUS 2004-2005 statistical report). The worldwide standard for grading and classification of these tumors is at present the WHO classification (Kleihues, P. and Cavenee, W. K., World Health Organization Classification of Tumours of the Nervous System, Lyon: WHO/IARC, 2000). Based on their histological appearance gliomas can be divided into astrocytic tumors, pure oligodendroglial tumors and mixed oligoastrocytic tumors. The latter two are grouped together as oligodendroglial tumors. The oligodendrogliomas comprise approximately 20% of all gliomas, and in comparison to most other gliomas, have a relatively long average survival time (5-12 years) after diagnosis (Okamoto, Y. et al., (2004) Acta Neuropathol. 28:28; Johannesen, T. B. et al. (2003) J. Neurosurg. 99: 854-862). Two malignancy grades are recognized in oligodendrocytic tumors, Grades II (low-grade) and III (anaplastic) (Collins, V. P. (2004) J. Neurol. Neurosurg. Psych. 75 Suppl. 2: ii2-ii11).

One of the striking differences between oligodendroglial tumors and other glioma subtypes is their sensitivity to therapy, especially radiotherapy and chemotherapy. The majority of oligodendroglial tumors respond favourably to chemotherapy with alkylating agents (either temolozomide or PCV, a combination therapy of procarbazine, CCNU, and vincristine), whereas other gliomas are often chemoresistant (Van den Bent, M. J. et al. (1998) Neurology 51: 1140-1145; Van den Bent, M. J. et al. (2003) J. Clin. Oncol. 21: 2525-2528). The most favourable clinical behaviour of oligodendral tumors renders it therefore important to correctly identify this subtype of gliomas. Unfortunately, histological classification and grading of gliomas has a significant subjective component. However, malignant gliomas can also be classified according to their gene expression profile (Nutt, C. L. et al. (2003) Cancer Res. 63: 1602-1607).

In oligodendroglial tumors, there is a strong correlation between chromosomal aberrations and response to treatment (chemotherapy and/or radiotherapy). For example, a common genomic aberration is a combined loss of the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q) (Okamoto, Y et al., 2004; Cairncross J. G. et al., (1998) J. Natl. Cancer Inst. 90:1473-1479; Kros J. M. et al., (1999) J. Pathol. 188:282-288; Smith J. S. et al., (1999) Oncogene 18:4144-4152; Thiessen B. et al., (2003) J. Neurooncol. 64:271-278; van den Bent, M. J. et al, (2003) Cancer 97:1276-1284). Loss of heterozygosity (LOH) on both chromosomal arms is correlated with a favourable response to therapy: A response to treatment is observed in 80-90% of oligodendroglial tumors with 1p LOH and in 25-30% without 1p LOH (Cairncross, J. G. et al, 1998; Thiessen, B. et al, 2003; van den Bent, M. J. et al., 2003). Other chromosomal aberrations observed at lower frequency include LOH on 10q and amplification of 7p11 (Kitange G. et al. (2004) Genes Chromosomes Cancer). These aberrations are correlated with poor prognosis and are negatively correlated with LOH on 1p and 19q. This correlation between response to treatment and chromosomal aberrations can therefore help identify chemosensitive oligodendroglial tumors. However, predicting the tumors' response to treatment by its chromosomal status also incorrectly classifies a significant percentage of tumors.

Thus, there still is a need for a more accurate prediction whether a patient with oligodendroglial tumors will be responsive to treatment and/or to predict the survival of a brain tumor patient. Expression profiling can be an alternative approach to identify oligodendroglial tumors that will benefit from therapeutic treatment. Although expression profiling has been performed on oligodendroglial tumors, mRNA expression has thus far not been correlated to treatment response.

The current inventors have now surprisingly shown that gene expression can be used to be correlated with susceptibility to treatment and increased survival, independent of the (1p and 19q) chromosomal status of the tumor. Further, also correlations have been found between gene expression and loss of 1p and 19q.

SUMMARY OF THE INVENTION

The invention now comprise a method for producing a classification scheme for oligodendroglial tumors comprising the steps of:

-   -   a) providing a plurality of reference samples, said reference         samples comprising cell samples from a plurality of reference         subjects suffering from oligodendroglial tumors, with known         responsiveness to therapy and survival;     -   b) providing reference profiles by establishing a gene         expression profile, matched with parameters for sensitivity to         treatment and survival for each of said reference samples         individually;     -   c) clustering said individual reference profiles according to a         statistical procedure, comprising:         -   (i) K-means clustering;         -   (ii) hierarchical clustering; and         -   (iii) Pearson correlation coefficient analysis; and     -   d) assigning an oligodendroglial tumor class according to         sensitivity to treatment and/or survival to each cluster.         Specifically in such a method the clustering of said gene         expression profiles is performed based on the information of         differentially-expressed genes and the sensitivity to treatment         and/or survival of the subject, wherein, preferably, the         clustering of said gene expression profiles with respect to         treatment response is performed based on the information of the         genes of Table 3, whereas the clustering of said gene expression         profiles with respect to survival is performed based on the         information of the genes of Table 4. Another embodiment of the         invention is a method for classifying an oligodendroglial tumor         of a subject suffering from an glial tumor, comprising the steps         of:     -   a) providing a classification scheme for oligodendroglial tumors         according to the above described method;     -   b) providing a subject profile by establishing a gene expression         profile for said subject;     -   c) clustering the subject profile together with reference         profiles;     -   d) determining in said scheme the clustered position of said         subject profile among the reference profiles, and     -   e) assigning to said glial tumor the oligodendroglial tumor         class that corresponds to said clustered position.         Preferably herein the gene expression profile with respect to         treatment response comprises the expression parameters of a set         of genes according to table 3, still more preferably 1 to 50         genes of the genes of table 3, whereas the gene expression         profile with respect to survival comprises the expression         parameters of a set of genes according to Table 4, more         preferably 1 tot 50 genes of the genes of Table 4. A further         embodiment of the invention is a method of determining the         prognosis for a subject suffering from an oligodendroglial         tumor, said method comprising the steps of:     -   a) providing a classification scheme for oligodendroglial tumors         by producing such a scheme according to the above described         method;     -   b) determining the prognosis for each olidendroglial tumor class         in said scheme based on clinical records for the subjects         comprised in said class;     -   c) establishing the oligodendroglial class of a subject         suffering from an oligodendroglial tumor by classifying the         oligodendroglial tumor in said subject according to a method         according to the invention, and     -   d) assigning to said subject the prognosis corresponding to the         established oligodendroglial tumor class of said subject.         Alternatively, the invention provides for a method of         determining the prognosis for a subject suffering from an         oligodendroglial tumor, said method comprising the steps of:     -   a) isolation of RNA from tumor cells of said subject;     -   b) preparation of antisense, biotinylated RNA to the RNA of step         a);     -   c) hybridisation of said antisense, biotinylated DNA on         Affymetrix U133A or U133 Plus2.0 GeneChips®;     -   d) normalising the measured values for the gene set of Table 3;     -   e) clustering the obtained data together with reference data,         obtained from a reference set of patients with known prognoses;         and     -   f) determining the prognosis on basis of the subgroup/cluster to         which the data of the subject are clustering.

In another embodiment, the invention provides for an oligonucleotide microarray of maximal 500 probesets, comprising at least 1, preferably at least 2, more preferably at least 25, still more preferably at least 100 oligonucleotide probes which each are capable of hybridizing under stringent conditions to different genes of the oligodendroglial tumor-associated genes selected from Table 3. Alternatively, the invention provides for an oligonucleotide microarray of maximal 500 probesets, comprising at least 1, preferably at least 2, more preferably at least 25, still more preferably at least 100 oligonucleotide probes which each are capable of hybridizing under stringent conditions to different genes of the oligodendroglial tumor-associated genes selected from Table 4.

In oligodendrogliomas there is a strong correlation between LOH on 1p/19q and response to treatment. In another embodiment, the invention provides for a method using an oligonucleotide microarray, which can be used for the determination of the presence of 1p LOH, 19q LOH or 1p/19q LOH. Particularly, the microarray for these determination should comprise the genesets of Table 5, 6 and 7, respectively. Accordingly, the invention also comprises an oligonucleotide microarray of maximal 500 probesets, comprising at least 1, preferably at least 2, more preferably at least 25, still more preferably at least 50 oligonucleotide probes which each are capable of hybridizing under stringent conditions to different genes of the oligodendroglial tumor-associated genes selected form Table 5, 6 and 7, respectively.

For the above described methods, the invention also comprises a kit-of-parts comprising an oligonucleotide microarray as described above and means for comparing a gene expression profile determined by using said microarray with a database of oligodendroglial tumor reference expression profiles.

LEGENDS TO THE FIGURES

FIG. 1.

Correlation plot of all samples. Samples are plotted against each other to determine the degree of similarity based on expressed genes. Red and blue denote high and low similarity respectively (scale bar). Below the correlation plot is a graphic representation of histological and patient data. Tissue: origin of sample

control cortex,

control white matter,

low-grade oligodendroglioma,

anaplastic oligodendroglioma. 1p, 19q, 10q LOH:

no LOH,

LOH. (LOH: loss of heterozygosity). EGFR ampl: amplification of the EFGR chromosomal locus:

no amplification,

amplification, Response: response to therapy complete

response,

partial response,

stable disease,

progressive disease. Surv tot: survival (years) from time of diagnosis.

>10,

7-10,

3-7,

<3.A: patient alive at time of analysis.

FIG. 2.

Principle components analysis (PCA) and hierarchical clustering of 60 probesets differentially expressed between oligodendroglial tumors with combined 1p and 19q LOH and those that have retained both 1p and 19q arms. A: samples are separated on their 1p and 19q chromosomal status by the first principle component axis (PCA1) whereas PCA2 separates control brain from anaplastic oligodendroglial tumors. The 1p and 19q status are color coded with

=no LOH on 1p and 19q,

=LOH on 1p and 19q, and

LOH on either 1p or 19q. B: Hierarchical clustering shows relative expression levels of individual genes (columns) plotted against individual tumor samples (rows). For clarity, control brain samples were omitted from the clustering analysis. Gene expression levels are color coded with red and green indicating high (+2) and low green (−2) expression respectively (on a log 2 scale). Dendrograms denote hierarchical clustering (Euclidian distance) of samples (top) and genes (left). The 1p and 19q status in indicated below the hierarchical clustering (

M=no LOH,

=LOH). As can be seen, hierarchical clustering clearly identifies two main subgroups associated with 1p/19q LOH.

FIG. 3.

PCA and hierarchical clustering based on 16 probesets differentially expressed between chemosensitive (CR+PR (complete response, partial response)) and chemoresistant (SD+PD, stable disease, progressive disease)) oligodendroglial tumors. A: samples are separated on their response to chemotherapy by the first principle component axis (PCA1) whereas PCA2 separates control brain from anaplastic oligodendroglial tumors. B: Hierarchical clustering based on 16 differentially expressed probesets. Relative expression levels of individual genes (columns) are plotted against individual tumor samples (rows). Gene expression levels are color coded with red and green indicating high (+1.8) and low green (−1.8) expression respectively. Dendrograms denote hierarchical clustering of samples (top) and genes (left) using Wards method. Hierarchical clustering separates tumors that fully respond to chemotherapy (CR) from tumors that do not respond (SD+PD). Furthermore, hierarchical clustering also clearly separates tumors with poor prognosis (subgroup III in FIG. 1) from other oligodendroglial tumors. Responses in oligodendroglial tumors are color coded with

complete response,

partial response,

stable disease,

progressive disease,

control brain. 1p chromosomal status is depicted as

no loss of 1p and

1p LOH.

FIG. 4.

PCA hierarchical clustering based on 103 probesets associated with survival after diagnosis. A: PCA identifies three main clusters of samples: oligodendroglial tumors with short survival, oligodendroglial tumors with long survival and control samples. Two low-grade samples (38 and 42, survival <10 years

) cluster between control and tumor samples. PCA analysis separates short vs. long survivors on the first principle component axis (PCA1) whereas control and tumor samples are separated by the second PCA axis. B: Hierarchical clustering based on 103 differentially expressed probesets. Relative expression levels of individual genes (columns) are plotted against individual tumor samples (rows). Gene expression levels are color coded with red and green indicating high (+2) and low green (−2) expression respectively. Dendrograms denote hierarchical clustering (Euclidian distance) of samples (top) and genes (left). Interestingly, the subgroups identified by hierarchical clustering are virtually identical to the subgroups that were identified by unsupervised clustering (FIG. 1). Survival after diagnosis is depicted as

>10 years survival,

<10 years survival,

<7 years survival,

<4 years survival,

patient still alive or,

control brain.

DETAILED DESCRIPTION OF THE INVENTION

The current inventors performed expression profiling on oligodendroglial tumors and correlated the results to response to treatment, survival after diagnosis and common chromosomal aberrations. One of the findings was that the chromosomal aberrations led to ˜50% expression of some but not all of the genes that had been deleted, Thus, this means that it is not straightforward to use the expression data of the genes from the 1p and 19q loci for the determination of the presence of a loss of heterozygosity (LOH) in these areas. Yet, the present inventors have found that a subset of genes, which show a reduced expression when one of the chromosomal arms 1p and 19q are deleted can be used to detect these chromosomal aberrations. The genes, which can distinguish between the presence or absence of 1p have been listed in Table 5, for LOH of 19q the genes are listed in Table 6, and Table 7 gives the list of discriminating genes for combined 1p and 19q LOH.

This means that gene expression data can be used for the determination of LOH of 1p and/or 19q. This is advantageous, since currently for said determination a FISH (Fluorescence In Situ Hybridisation) or LOH (loss of heterozygosity)-PCR is used, which are specialised tests, using labelled probes. Now it has been established that a similar determination can be achieved by using standard array technology.

Further, the present study shows that the currently used predictions, based on loss of 1p, were only correctly assigned to the correct treatment response group in 20/28 (71%) of the cases, both because of positive and negative misclassifications

The term “classifying” is used in its art-recognized meaning and thus refers to arranging or ordering items, i.c. gene expression profiles, by classes or categories or dividing them into logically hierarchical classes, subclasses, and sub-subclasses based on the characteristics they have in common and/or that distinguish them. In particular “classifying” refers to assigning, to a class or kind, an unclassified item. A “class” then being a grouping of items, based on one or more characteristics, attributes, properties, qualities, effects, parameters, etc., which they have in common, for the purpose of classifying them according to an established system or scheme.

The term “classification scheme” is used in its art-recognized meaning and thus refers to a list of classes arranged according to a set of pre-established principles, for the purpose of organizing items in a collection or into groups based on their similarities and differences.

The term “clustering” refers to the activity of collecting, assembling and/or uniting into a cluster or clusters items with the same or similar elements, a “cluster” referring to a group or number of the same or similar items, i.c. gene expression profiles, gathered or occurring closely together based on similarity of characteristics. “Clustered” indicates an item has been subjected to clustering.

The term “clustered position” refers to the location of an individual item, i.c. a gene expression profile, in amongst a number of clusters, said location being determined by clustering said item with at least a number of items from known clusters.

The process of clustering used in a method of the present invention may be any mathematical process known to compare items for similarity in characteristics, attributes, properties, qualities, effects, parameters, etc. Statistical analysis, such as for instance multivariance analysis, or other methods of analysis may be used. Preferably methods of analysis such as self-organising maps, hierarchical clustering, multidimensional scaling, principle component analysis, supervised learning, k-nearest neighbours, support vector machines, discriminant analysis, partial least square methods and/or Pearson's correlation coefficient analysis are used. In another preferred embodiment of a method of the present invention Pearson's correlation coefficient analysis, significance analysis of microarrays (SAM) and/or prediction analysis of microarrays (PAM) are used to cluster gene expression profiles according to similarity. A highly preferred method of clustering comprises similarity clustering of gene expression profiles wherein the expression level of differentially-expressed genes, having markedly lower or higher expression than the geometric mean expression level determined for all genes in all profiles to be clustered, is log(2) transformed, and wherein the transformed expression levels of all differentially-expressed genes in all profiles to be clustered is clustered by using K-means. A numerical query may then be used to select a subset of genes used in the process of hierarchical clustering (Eisen et al., 1998), thus, numerical queries may be run to select differentially expressed genes relative to the calculated geometric mean to select a smaller group of genes for hierarchical clustering.

Unsupervised sample clustering using genes obtained by numerical or threshold filtering is used to identify discrete clusters of samples as well as the gene-signatures associated with these clusters. The term gene signatures is used herein to refer to the set of genes that define the discrete position of the cluster apart from all other clusters, and includes cluster-specific genes. A numerical or threshold filtering is used to select genes for the analysis that are most likely of diagnostic relevance. Hierarchical clustering allows for visualization of large variation in gene expression across samples or present in most samples, and these genes could be used for unsupervised clustering so that clustering results are not affected by the noise from absent or non-changed genes.

Thus, while K-means clustering may be performed on all genes, the Pearson correlation is preferably calculated based on a subset of genes. Generally speaking the larger the threshold for accepting a deviation or change from the geometric mean, the smaller the number of genes that is selected by this filtering procedure. Different cut-off or threshold values were used to prepare lists with different numbers of genes. The higher the number of genes selected and included on such lists, the more noise is generally encountered within the dataset, because there will be a relatively large contribution of non-tumor pathway related genes in such lists. The filtering and selection procedure is preferably optimized such that the analysis is performed on as many genes as possible, while minimizing the noise.

All genes with changed expression values in at least one sample higher than or equal to 1.5 times the log(2) transformed expression values and genes with changed expression values lower than or equal to −1.5 times the log(2) transformed expression value means are selected for unsupervised clustering.

The subset of genes showing a markedly higher or lower expression than the geometric mean may for instance be a value that is more than 1.5 times the geometric mean value, preferably more than 2 times the geometric mean value, Likewise, a markedly lower expression than the geometric mean expression level may for instance be a value that is less than 0.8 times the geometric mean value, preferably less than 0.6 times the geometric mean value.

Independently (see FIG. 1) a Pearson correlation coefficient analysis was performed on the samples (1881 probesets), which showed that clustering of patients is feasible.

The present invention now provides several methods to accurately identify known as well as newly discovered diagnostically, prognostically and therapeutically relevant subgroups of oligodendroglial tumors, as well as methods that can predict if treatment is likely to be effective. The basis of these methods resides in the measurement of (oligodendroglial tumor-specific) gene expression in subjects suffering from brain tumors. The methods and compositions of the invention thus provide tools useful in choosing a therapy for brain tumor patients, including methods for assigning an brain tumor patient to a brain tumor class or cluster, methods of choosing a therapy for a brain tumor patient, and methods of determining the survival prognosis for a brain tumor patient.

The methods of the invention comprise in various aspects the steps of establishing a gene expression profile of subject samples, for instance of reference subjects suffering from a brain tumor or of a subject diagnosed or classified as having a brain tumor. The expression profiles of the present invention are generated from samples from subjects having a brain tumor. The samples from the subject used to generate the expression profiles of the present invention can be derived from a tumor biopsy, wherein the sample comprises preferably more than 75% tumor cells.

“Gene expression profiling” or “expression profiling” is used herein in its art-recognised meaning and refers to a method for measuring the transcriptional state (mRNA) or the translational state (protein) of a plurality of genes in a cell. Depending on the method used, such measurements may involve the genome-wide assessment of gene expression, but also the measurement of the expression level of selected genes, resulting in the establishment of a “gene expression profile” or “expression profile”, which terms are used in that meaning hereinbelow. As used herein, an “expression profile” comprises one or more values corresponding to a measurement of the relative abundance of a gene expression product. Such values may include measurements of RNA levels or protein abundance. Thus, the expression profile can comprise values representing the measurement of the transcriptional state or the translational state of the gene. In relation thereto, reference is made to U.S. Pat. Nos. 6,040,138, 5,800,992, 6,020,135, 6,344,316, and 6,033,860.

The transcriptional state of a sample includes the idensities and relative abundance of the RNA species, especially mRNAs present in the sample. Preferably, a substantial fraction of all constituent RNA species in the sample are measured, but at least a sufficient fraction to characterize the transcriptional state of the sample is measured. The transcriptional state can be conveniently determined by measuring transcript abundance by any of several existing gene expression technologies.

Translational state includes the identities and relative abundance of the constituent protein species in the sample. As is known to those of skill in the art, the transcriptional state and translational state are often related.

Each value in the expression profiles as determined and embodied in the present invention is a measurement representing the absolute or the relative expression level of a differentially-expressed gene. The expression levels of these genes may be determined by any method known in the art for assessing the expression level of an RNA or protein molecule in a sample. For example, expression levels of RNA may be monitored using a membrane blot (such as used in hybridization analysis such as Northern, Southern, dot, and the like), or microwells, sample tubes, gels, beads or fibers (or any solid support comprising bound nucleic acids). See U.S. Pat. Nos. 5,770,722, 5,874,219, 5,744,305, 5,677,195 and 5,445,934, to which explicit reference is made. The gene expression monitoring system may also comprise nucleic acid probes in solution.

In one embodiment of the invention, microarrays are used to measure the values to be included in the expression profiles. Microarrays are particularly well suited for this purpose because of the reproducibility between different experiments. DNA microarrays provide one method for the simultaneous measurement of the expression levels of large numbers of genes. Each array consists of a reproducible pattern of capture probes attached to a solid support. Labeled RNA or DNA is hybridized to complementary probes on the array and then detected by laser scanning. Hybridization intensities for each probe on the array are determined and converted to a quantitative value representing relative gene expression levels. See, the Experimental section. See also, U.S. Pat. Nos. 6,040,138, 5,800,992 and 6,020,135, 6,033,860, and 6,344,316, to which explicit reference is made. High-density oligonucleotide arrays are particularly useful for determining the gene expression profile for a large number of RNA's in a sample.

In one approach, total RNA isolated from the sample is converted to labeled cRNA and then hybridized to an oligonucleotide array. Each sample is hybridized to a separate array. Relative transcript levels are calculated by reference to appropriate controls present on the array and in the sample. See, for example, the Experimental section.

In another embodiment, the values in the expression profile are obtained by measuring the abundance of the protein products of the differentially-expressed genes. The abundance of these protein products can be determined, for example, using antibodies specific for the protein products of the differentially-expressed genes. The term “antibody” as used herein refers to an immunoglobulin molecule or immunologically active portion thereof, i.e., an antigen-binding portion. Examples of immunologically active portions of immunoglobulin molecules include F(ab) and F(ab′)2 fragments which can be generated by treating the antibody with an enzyme such as pepsin. The antibody can be a polyclonal, monoclonal, recombinant, e.g., a chimeric or humanized, fully human, non-human, e.g., murine, or single chain antibody. In a preferred embodiment it has effector function and can fix complement. The antibody can be coupled to a toxin or imaging agent. A full-length protein product from a differentially-expressed gene, or an antigenic peptide fragment of the protein product can be used as an immunogen. Preferred epitopes encompassed by the antigenic peptide are regions of the protein product of the differentially-expressed gene that are located on the surface of the protein, e.g., hydrophilic regions, as well as regions with high antigenicity. The antibody can be used to detect the protein product of the differentially-expressed gene in order to evaluate the abundance and pattern of expression of the protein. These antibodies can also be used diagnostically to monitor protein levels in tissue as part of a clinical testing procedure, e.g., to, for example, determine the efficacy of a given therapy. Detection can be facilitated by coupling (i.e., physically linking) the antibody to a detectable substance (i.e., antibody labeling). Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, (3-galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride, quantum dots or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin, and examples of suitable radioactive material include ¹²⁵I, ¹³¹I, ³⁵S or ³H.

Once the values comprised in the subject expression profile and the reference expression profile or expression profiles are established, the subject profile is compared to the reference profile to determine whether the subject expression profile is sufficiently similar to the reference profile. Alternatively, the subject expression profile is compared to a plurality of reference expression profiles to select the reference expression profile that is most similar to the subject expression profile. Any method known in the art for comparing two or more data sets to detect similarity between them may be used to compare the subject expression profile to the reference expression profiles. In some embodiments, the subject expression profile and the reference profile are compared using a supervised learning algorithm such as the support vector machine (SVM) algorithm, prediction by collective likelihood of emerging patterns (PCL) algorithm, the k-nearest neighbour algorithm, or the Artificial Neural Network algorithm. To determine whether a subject expression profile shows “statistically significant similarity” or “sufficient similarity” to a reference profile, statistical tests may be performed to determine whether the similarity between the subject expression profile and the reference expression profile is likely to have been achieved by a random event. Any statistical test that can calculate the likelihood that the similarity between the subject expression profile and the reference profile results from a random event can be used. The accuracy of assigning a subject to an oligodendroglial tumor class based on similarity between differentially-expressed genes is affected largely by the heterogeneity within the patient population, as is reflected by the deviation from the geometric mean. Therefore, when more accurate diagnoses are required, the stringency in evaluating the similarity between the subject and the reference profile should be increased by changing the numerical query.

The method used for comparing a subject expression profile to one or more reference profiles is preferably carried out by re-running the subsequent analyses in a (n+1) modus by performing clustering methods as described herein. Also, in order to identify the oligodendroglial tumor class reference profile that is most similar to the subject expression profile, as performed in the methods for establishing the oligodendroglial tumor class of a subject having a brain tumor, i.e. by diagnosing presence of an oligodendroglial tumor in a subject or by classifying the oligodendroglial tumor in a subject, profiles are clustered according to similarity and it is determined whether the subject profile corresponds to a known class of reference profiles. In assigning a subject oligodendroglial tumor to a specific oligodendroglial tumor class for instance, this method is used wherein the clustered position of the subject profile, obtained after performing the clustering analysis of the present invention, is compared to any known oligodendroglial tumor class. If the clustered position of the subject profile is within a cluster of reference profiles, i.e. forms a cluster therewith after performing the similarity clustering method, it is said that the oligodendroglial tumor of the subject corresponds to the oligodendroglial tumor class of reference profiles.

In some embodiments of the present invention, the expression profiles comprise values representing the expression levels of genes that are differentially-expressed in oligodendroglial tumor classes. The term “differentially-expressed” as used herein means that the measured expression level of a particular gene in the expression profile of one subject differs at least n-fold from the geometric mean calculated from all patient profiles. The expression level may be also be up-regulated or down-regulated in a sample from a subject in comparison with a sample from a normal brain sample, or in comparison with the mean of all oligodendroglial tumor patients. Examples of genes that are differentially expressed in brain tumor patients which respond to therapy and brain tumor patients which do not respond to therapy, short vs. long survivors and 1p and/or 19q LOH vs. no loss are listed in Tables 3, 4, 5, 6 and 7.

It should be noted that many genes will occur, of which the measured expression level differs at least n-fold from the geometric mean expression level for that gene of all reference profiles. This may for instance be due to the different physiological state of the measured cells, to biological variation or to the presence of other diseased states. Therefore, the presence of a differentially-expressed gene is not necessarily informative for determining the presence of different oligodendroglial tumor classes, nor is every differentially-expressed gene suitable for performing diagnostic tests. Moreover, a cluster-specific differential gene expression, as defined herein, is most likely to be informative only in a test among subjects having brain tumors. Therefore, a diagnostic test performed by using cluster-specific gene detection should preferably be performed on a subject in which the presence of an oligodendroglial tumor is confirmed. This confirmation may for instance be obtained by standard macroscopic and microscopic detection methods.

The present invention provides groups of genes that are differentially-expressed in diagnostic oligodendroglial tumor biopsy and surgical resection samples of patients in different therapeutic groups (i.e. responders/non-responders, or short-survivors/long-survivors). Values representing the expression levels of the nucleic acid molecules detected by the probes were analyzed as described in the Experimental section using Omniviz and SAM analysis tools. Omniviz software was used to perform all clustering steps such as K-means, Hierarchical and Pearson correlation tests. SAM was used specifically to identify the genes underlying the clinically relevant groups identified in the Pearson correlation analysis. PAM is used to decide the minimum number of genes necessary to diagnose all individual patients within the given groups of the Pearson correlation.

In short, expression profiling was carried out on biopsy material from 28 brain tumor patients. Unsupervised clustering was used to identify novel (sub)groups within the Pearson correlation following the hierarchical clustering. After running the SAM analysis the diagnostic gene-signatures (incl. cluster-specific genes) were obtained.

It appeared that a clustering separating the different groups of patients could be performed on the basis of differential expression of a plurality of genes.

The present invention thus provides a method of classifying oligodendroglial tumors. Using this method, a total of 28 brain tumor samples analysed on a DNA microarray consisting of 54675 probe sets, representing approximately 23000 genes, could be classified. The classification into patient groups was performed on the basis of strong correlation between their individual differential expression profiles within a group for 1881 probe sets (˜1413 genes). The methods used to analyze the expression level values to identify differentially-expressed genes were employed such that optimal results in clustering, i.e. unsupervised ordering, were obtained. The genes that defined the position or clustering of these patient groups could be determined and the minimal sets of genes required to accurately predict the prognostically important classes could be derived. It should be understood that the method for classifying oligodendroglial tumors according to the present invention may result in a distinct pattern and therefore in a different classification scheme when other (numbers of) subjects are used as reference, or when other types of oligonucleotide microarrays for establishing gene expression profiles are used.

The present invention thus provides a comprehensive classification of oligodendroglial tumors covering previously identified therapeutically defined classes. Further analysis of classes by significance analysis of microarrays (SAM) to determine the minimum number of genes that defined or predicted these classes resulted in the establishment of cluster-specific genes or signature genes.

The methods of the present invention comprise in some aspects the step of defining cluster-specific genes by selecting those genes of which the expression level characterizes the clustered position of the corresponding oligodendroglial tumor class within a classification scheme of the present invention. Such cluster-specific genes are selected preferably on the basis of SAM analysis. This method of selection comprises the following.

The methods of the present invention comprise in some aspects the step of establishing whether the level of expression of cluster-specific genes in a subject shares sufficient similarity to the level of expression that is characteristic for an individual oligodendroglial tumor class. This step is necessary in determining the presence of that particular oligodendroglial tumor class in a subject under investigation, in which case the expression of that gene is used as a prognostic marker. Whether the level of expression of cluster-specific genes in a subject shares sufficient similarity to the level of expression of that particular gene in an individual oligodendroglial tumor class may for instance be determined by setting a threshold value.

The present invention also reveals genes with a high differential level of expression in specific oligodendroglial tumor classes compared to the geometric mean of all reference subjects. These highly differentially-expressed genes are selected from the genes shown in Tables 3-7, These genes and their expression products are useful as markers to predict the responsiveness to treatment, 1p and/or 19q loss of heterozygosity or survival chance in a patient. Antibodies or other reagents or tools may be used to detect the presence of these markers of brain tumor.

The present invention also reveals gene expression profiles comprising values representing the expression levels of genes in the various identified oligodendroglial tumor classes. In a preferred embodiment, these expression profiles comprise the values representing the differential expression levels. Thus, in one embodiment the expression profiles of the invention comprise one or more values representing the expression level of a gene having differential expression in a defined oligodendroglial tumor class. Each expression profile contains a sufficient number of values such that the profile can be used to distinguish treatment response groups, to distinguish groups with different survival, an to distinguish groups with 1p and/or 19q LOH. The expression profile comprises more than one or two values corresponding to a differentially-expressed gene, for example at least 3 values, at least 4 values, at least 5 values, at least 6 values, at least 7 values, at least 8 values, at least 9 values, at least 10 values, at least 11 values, at least 12 values, at least 13 values, at least 14 values, at least 15 values, at least 16 values, at least 17 values, at least 18 values, at least 19 values, at least 20 values, at least 22 values, at least 25 values, at least 27 values, at least 30 values, at least 35 values, at least 40 values, at least 45 values, at least 50 values, at least 75 values, at least 100 values, at least 125 values, at least 150 values, at least 175 values, at least 200 values, at least 250 values, at least 300 values, at least 400 values, at least 500 values, at least 600 values, at least 700 values, at least 800 values, at least 900 values, at least 1000 values, at least 1200 values, at least 1500 values, or at least 2000 or more values.

It is recognized that the diagnostic accuracy of assigning a subject to an oligodendroglial tumor class will vary based on the number of values contained in the expression profile. Generally, the number of values contained in the expression profile is selected such that the diagnostic accuracy is at least 85%, at least 87%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99%, as calculated using methods described elsewhere herein, with an obvious preference for higher percentages of diagnostic accuracy.

It is recognized that the diagnostic accuracy of assigning a subject to an oligodendroglial tumor class will vary based on the strength of the correlation between the expression levels of the differentially-expressed genes within that specific oligodendroglial tumor class. When the values in the expression profiles represent the expression levels of genes whose expression is strongly correlated with that specific oligodendroglial tumor class, it may be possible to use fewer number of values (genes) in the expression profile and still obtain an acceptable level of diagnostic or prognostic accuracy.

The strength of the correlation between the expression level of a differentially-expressed gene and a specific oligodendroglial tumor class may be determined by a statistical test of significance. For example, the chi square test used to select genes in some embodiments of the present invention assigns a chi square value to each differentially-expressed gene, indicating the strength of the correlation of the expression of that gene to a specific oligodendroglial tumor class. Similarly, the T-statistics metric and the Wilkins' metric both provide a value or score indicative of the strength of the correlation between the expression of the gene and its specific oligodendroglial tumor class. These scores may be used to select the genes of which the expression levels have the greatest correlation with a particular oligodendroglial tumor class to increase the diagnostic or prognostic accuracy of the methods of the invention, or in order to reduce the number of values contained in the expression profile while maintaining the diagnostic or prognostic accuracy of the expression profile. Preferably, a database is kept wherein the expression profiles of reference subjects are collected and to which database new profiles can be added and clustered with the already existing profiles such as to provide the clustered position of said new profile among the already present reference profiles. Furthermore, the addition of new profiles to the database will improve the diagnostic and prognostic accuracy of the methods of the invention. Preferably, in a method of the present invention SAM or PAM analysis tools are used to determine the strength of such correlations.

The methods of the invention comprise the steps of providing an expression profile from a sample from a subject affected by oligodendroglial tumor and comparing this subject expression profile to one or more reference profiles that are associated with a particular oligodendroglial tumor class with a known prognosis, or a class with a favourable response to therapy. By identifying the oligodendroglial tumor class reference profile that is most similar to the subject expression profile, e.g. when their clustered positions fall together, the subject can be assigned to an oligodendroglial tumor class. The oligodendroglial class assigned is that with which the reference profile(s) are associated. Similarly, the prognosis of a subject affected by an oligodendroglial tumor can be predicted by determining whether the expression profile from the subject is sufficiently similar to a reference profile associated with an established prognosis, such as a good prognosis or a bad prognosis. Whenever a subject's expression profile can be assigned to one of the reference profile(s), a preferred intervention strategy, or therapeutic treatment can then be proposed for said subject, and said subject can be treated according to said assigned strategy. As a result, treatment of a subject with an oligodendroglial can be optimized according to the identified cluster.

In one aspect, the present invention provides a method of determining the prognosis for a brain tumor patient, said method comprising the steps of providing a classification scheme for oligodendroglial tumors by producing such a scheme according to a method of the invention for reference subjects having known post-therapy lifetimes. The present invention provides for the assignment of the various clinical data recorded to reference subjects affected by brain tumors. This assignment preferably occurs in a database. This has the advantage that once a new subject is identified as belonging to a particular oligodendroglial tumor class, then the prognosis that is assigned to that class may be assigned to that subject.

The present invention provides compositions that are useful in determining the gene expression profile for a subject affected by an oligodendroglial tumor and selecting a reference profile that is similar to the subject expression profile. These compositions include arrays comprising a substrate having capture probes that can bind specifically to nucleic acid molecules that are differentially-expressed in oligodendroglial tumor classes. Also provided is a computer-readable medium having digitally encoded reference profiles useful in the methods of the claimed invention.

The present invention provides arrays comprising capture probes for detection of polynucleotides (transcriptional state) or for detection of proteins (translational state) in order to detect differentially-expressed genes of the invention. By “array” is intended a solid support or substrate with peptide or nucleic acid probes attached to said support or substrate. Arrays typically comprise a plurality of different nucleic acid or peptide capture probes that are coupled to a surface of a substrate in different, known locations. These arrays, also described as “microarrays” or colloquially “chips” have been generally described in the art, and reference is made U.S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195, 6,040,193, 5,424,186, 6,329,143, and 6,309,831 and Fodor et al. (1991) Science 251:767-77. These arrays may generally be produced using mechanical synthesis methods or light directed synthesis methods which incorporate a combination of photolithographic methods and solid phase synthesis methods. Typically, “oligonucleotide microarrays” will be used for determining the transcriptional state, whereas “peptide microarrays” will be used for determining the translational state of a cell.

“Nucleic acid” or “oligonucleotide” or “polynucleotide” or grammatical equivalents used herein means at least two nucleotides covalently linked together. Oligonucleotides are typically from about 5, 6, 7, 8, 9, 10, 12, 15, 25, 30, 40, 50 or more nucleotides in length, up to about 100 nucleotides in length. Nucleic acids and polynucleotides are a polymers of any length, including longer lengths, e.g., 200, 300, 500, 1000, 2000, 3000, 5000, 7000, 10,000, etc. A nucleic acid of the present invention will generally contain phosphodiester bonds, although in some cases, nucleic acid analogs are included that may have alternate backbones, comprising, e.g., phosphoramidate, phosphorothioate, phosphorodithioate, or O-methylphophoroamidite linkages (see Eckstein, Oligonucleotides and Analogues: A Practical Approach, Oxford University Press); and peptide nucleic acid backbones and linkages. Other analog nucleic acids include those with positive backbones; non-ionic backbones, and non-ribose backbones, including those described in U.S. Pat. Nos. 5,235,033 and 5,034,506, and Chapters 6 and 7, ASC Symposium Series 580, Carbohydrate Modifications in Antisense Research, Sanghui & Cook, eds. Nucleic acids containing one or more carbocyclic sugars are also included within one definition of nucleic acids. Modifications of the ribose-phosphate backbone may be done for a variety of reasons, e.g. to increase the stability and half-life of such molecules in physiological environments or as probes on a biochip. Mixtures of naturally occurring nucleic acids and analogues can be made; alternatively, mixtures of different nucleic acid analogues, and mixtures of naturally occurring nucleic acids and analogues may be made.

Particularly preferred are peptide nucleic acids (PNA) which includes peptide nucleic acid analogues. These backbones are substantially non-ionic under neutral conditions, in contrast to the highly charged phosphodiester backbone of naturally occurring nucleic acids. This results in two advantages. First, the PNA backbone exhibits improved hybridization kinetics. PNAs have larger changes in the melting temperature (T_(m)) for mismatched versus perfectly matched basepairs. DNA and RNA typically exhibit a 2-4° C. drop in T_(m) for an internal mismatch. With the non-ionic PNA backbone, the drop is closer to 7-9° C. Similarly, due to their non-ionic nature, hybridization of the bases attached to these backbones is relatively insensitive to salt concentration. In addition, PNAs are not degraded by cellular enzymes, and thus can be more stable.

The nucleic acids may be single stranded or double stranded, as specified, or contain portions of both double stranded or single stranded sequence. As will be appreciated by those in the art, the depiction of a single strand also defines the sequence of the complementary strand; thus the sequences described herein also provide the complement of the sequence. The nucleic acid may be DNA, both genomic and cDNA, RNA or a hybrid, where the nucleic acid may contain combinations of deoxyribo- and ribo-nucleotides, and combinations of bases, including uracil, adenine, thymine, cytosine, guanine, inosine, xanthine hypoxanthine, isocytosine, isoguanine, etc.

“Transcript” typically refers to a naturally occurring RNA, e.g., a pre-mRNA, hnRNA, or mRNA. As used herein, the term “nucleoside” includes nucleotides and nucleoside and nucleotide analogues, and modified nucleosides such as amino modified nucleosides. In addition, “nucleoside” includes non-naturally occurring analogue structures. Thus, e.g. the individual units of a peptide nucleic acid, each containing a base, are referred to herein as a nucleoside.

As used herein a “nucleic acid probe or oligonucleotide” is defined as a nucleic acid capable of binding to a target nucleic acid of complementary sequence through one or more types of chemical bonds, usually through complementary base pairing, usually through hydrogen bond formation. As used herein, a probe may include natural (i.e., A, G, C, or T) or modified bases (7-deazaguanosine, inosine, etc.). In addition, the bases in a probe may be joined by a linkage other than a phosphodiester bond, so long as it does not functionally interfere with hybridization. Thus, e.g., probes may be peptide nucleic acids in which the constituent bases are joined by peptide bonds rather than phosphodiester linkages. It will be understood by one of skill in the art that probes may bind target sequences lacking complete complementarity with the probe sequence depending upon the stringency of the hybridization conditions. The probes are preferably directly labeled such as with isotopes, chromophores, lumiphores, chromogens, or indirectly labeled such as with biotin to which a streptavidin complex may later bind or with enzymatic labels. By assaying for the hybridization of the probe to its target nucleic acid sequence, one can detect the presence or absence of the select sequence or subsequence. Diagnosis or prognosis may be based at the genomic level, or at the level of RNA or protein expression.

The skilled person is capable of designing oligonucleotide probes that can be used in diagnostic methods of the present invention. Preferably, such probes are immobilised on a solid surface as to form an oligonucleotide microarray of the invention. The oligonucleotide probes useful in methods of the present invention are capable of hybridizing under stringent conditions to oligodendroglial tumor-associated nucleic acids, such as to one or more of the genes selected from Table 2 or Table 3.

Techniques for the synthesis of arrays using mechanical synthesis methods are described in, e.g., U.S. Pat. No. 5,384,261, to which reference is made herein. Although a planar array surface is preferred, the array may be fabricated on a surface of virtually any shape or even a multiplicity of surfaces. Arrays may be peptides or nucleic acids on beads, gels, polymeric surfaces, fibers such as fiber optics, glass or any other appropriate substrate, for the purpose of which reference is made to U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992. Arrays may be packaged in such a manner as to allow for diagnostics or other manipulation of an all-inclusive device. Reference is for example made to U.S. Pat. Nos. 5,856,174 and 5,922,591.

The arrays provided by the present invention comprise capture probes that can specifically bind a nucleic acid molecule that is differentially-expressed in oligodendroglial tumor classes. These arrays can be used to measure the expression levels of nucleic acid molecules to thereby create an expression profile for use in methods of determining the therapeutic treatment and prognosis for oligodendroglial tumor patients.

In some embodiments, each capture probe in the array detects a nucleic acid molecule selected from the nucleic acid molecules designated in Tables 2 or Table 3. The designated nucleic acid molecules include those differentially-expressed in oligodendroglial tumor classes.

The arrays of the invention comprise a substrate having a plurality of addresses, where each address has a capture probe that can specifically bind a target nucleic acid molecule. The number of addresses on the substrate varies with the purpose for which the array is intended. The arrays may be low-density arrays or high-density arrays and may contain 4 or more, 8 or more, 12 or more, 16 or more, 20 or more, 24 or more, 32 or more, 48 or more, 64 or more, 72 or more 80 or more, 96, or more addresses, or 192 or more, 288 or more, 384 or more, 768 or more, 1536 or more, 3072 or more, 6144 or more, 9216 or more, 12288 or more, 15360 or more, or 18432 or more addresses. In some embodiments, the substrate has no more than 12, 24, 48, 96, or 192, or 384 addresses, no more than 500, 600, 700, 800, or 900 addresses, or no more than 1000, 1200, 1600, 2400, or 3600 addresses.

The invention also provides a computer-readable medium comprising one or more digitally encoded expression profiles, where each profile has one or more values representing the expression of a gene that is differentially-expressed in an oligodendroglial tumor class. The preparation and use of such profiles is well within the reach of the skilled person (see e.g. WO 03/083140). In some embodiments, the digitally-encoded expression profiles are comprised in a database. See, for example, U.S. Pat. No. 6,308,170.

The present invention also provides kits useful for predicting the responsiveness to therapy in subjects affected by an oligodendroglial tumor. These kits comprise an array and a computer readable medium. The array comprises a substrate having addresses, where each address has a capture probe that can specifically bind a nucleic acid molecule (by using an oligonucleotide array) or a peptide (by using a peptide array) that is differentially-expressed in an oligodendroglial tumor class. The results are converted into a computer-readable medium that has digitally-encoded expression profiles containing values representing the expression level of a nucleic acid molecule detected by the array.

By using the array described above, the amounts of various kinds of nucleic acid molecules contained in a nucleic acid sample can be simultaneously determined. In addition, there is an advantage such that the determination can be carried out even with a small amount of the nucleic acid sample. For instance, mRNA in the sample is labeled, or labeled cDNA is prepared by using mRNA as a template, and the labeled mRNA or cDNA is subjected to hybridization with the array, so that mRNAs being expressed in the sample are simultaneously detected, whereby their expression levels can be determined.

Genes each of which expression is altered due to an oligodendroglial tumor can be found by determining expression levels of various genes in the tumor cells and classified into certain types as described above and comparing the expression levels with the expression level in a control tissue.

The method for determining the expression levels of genes is not particularly limited, and any of techniques for confirming alterations of the gene expressions mentioned above can be suitably used. Among all, the method using the array is especially preferable because the expressions of a large number of genes can be simultaneously determined. Suitable arrays are commercially available, e.g., from Affymetrix.

For instance, mRNA is prepared from tumor cells, and then reverse transcription is carried out with the resulting mRNA as a template. During this process, labeled cDNA can be obtained by using, for instance, any suitable labeled primers or labeled nucleotides.

As to the labeling substance used for labeling, there can be used substances such as radioisotopes, fluorescent substances, chemiluminescent substances and substances with fluophor, and the like. For instance, the fluorescent substance includes Cy2, Fluor X, Cy3, Cy3.5, Cy5, Cy5.5, Cy7, fluorescein isothiocyanate (FITC), Texas Red, Rhodamine and the like. In addition, it is desired that samples to be tested (cancer samples to be tested in the present selection method) and a sample to be used as a control are each labeled with different fluorescent substances, using two or more fluorescent substances, from the viewpoint of enabling simultaneous detection. Here, labeling of the samples is carried out by labeling mRNA in the samples, cDNA derived from the mRNA, or nucleic acids produced by transcription or amplification from cDNA.

Next, the hybridization is carried out between the above-mentioned labeled cDNA and the array to which a nucleic acid corresponding to a suitable gene or its fragment is immobilized. The hybridization may be performed according to any known processes under conditions that are appropriate for the array and the labeled cDNA to be used. For instance, the hybridization can be performed under the conditions described in Molecular Cloning, A laboratory manual, 2nd ed., 9.52-9.55 (1989).

The hybridization between the nucleic acids derived from the samples and the array is carried out, under the above-mentioned hybridization conditions. When much time is needed for the time period required for procedures from the collection of samples to the determination of expression levels of genes, the degradation of mRNA may take place due to actions of ribonuclease. In order to determine the difference in the gene expressions in the samples to be tested (i.e., tumor cells or biopsies from oligodendroglial tumor patients) and the gene expressions in a control sample, it is preferable that the mRNA levels in both of these samples are adjusted using a standard gene with relatively little alterations in expressions.

Thereafter, by comparing the hybridization results of the samples to be tested with those of the control sample, genes exhibiting differential expression levels in both samples can be detected. Concretely, a signal which is appropriate depending upon the method of labeling used is detected for the array which is subjected to hybridization with the nucleic acid sample labeled by the method as described above, whereby the expression levels in the samples to be tested can be compared with the expression level in the control sample for each of the genes on the array.

The genes thus obtained which have a significant difference in signal intensities are genes each of which expression is altered specifically for certain oligodendroglial tumor classes.

The present invention also provides a computer-readable medium comprising a plurality of digitally-encoded expression profiles wherein each profile of the plurality has a plurality of values, each value representing the expression of a gene that is differentially-expressed in an oligodendroglial tumor class. The invention also provides for the storage and retrieval of a collection of data relating to oligodendroglial tumor specific gene expression data of the present invention, including sequences and expression levels in a computer data storage apparatus, which can include magnetic disks, optical disks, magneto-optical disks, DRAM, SRAM, SGRAM, SDRAM, RDRAM, DDR RAM, magnetic bubble memory devices, and other data storage devices, including CPU registers and on-CPU data storage arrays. Typically, the data records are stored as a bit pattern in an array of magnetic domains on a magnetizable medium or as an array of charge states or transistor gate states, such as an array of cells in a DRAM device (e.g., each cell comprised of a transistor and a charge storage area, which may be on the transistor).

For use in diagnostic, research, and therapeutic applications suggested above, kits are also provided by the invention. In the diagnostic and research applications such kits may include any or all of the following: assay reagents, buffers, oligodendroglial tumor class-specific nucleic acids or antibodies, hybridization probes and/or primers, antisense polynucleotides, ribozymes, arrays, antibodies, Fab fragments, capture peptides etc. In addition, the kits may include instructional materials containing directions (i.e., protocols) for the practice of the methods of this invention. While the instructional materials typically comprise written or printed materials, they are not limited to such. Any medium capable of storing such instructions and communicating them to an end user is contemplated by this invention. Such media include, but are not limited to electronic storage media (e.g., magnetic discs, tapes, cartridges, chips), optical media (e.g., CD ROM), and the like. Such media may include addresses to internet sites that provide such instructional materials. One such internet site may provide a database of oligodendroglial tumor reference expression profiles useful for performing similarity clustering of a newly determined subject expression profiles with a large set of reference profiles of oligodendroglial subjects comprised in said database. Preferably the database includes clinically relevant data such as patient prognosis, effects of methods of treatment and other characteristics relating to the oligodendroglial tumor patient.

The invention encompasses for instance kits comprising an array of the invention and a computer-readable medium having digitally-encoded reference profiles with values representing the expression of nucleic acid molecules detected by the arrays. These kits are useful for assigning a brain tumor patient subject to an oligodendroglial tumor class.

In a preferred embodiment a kit-of-parts according to the invention comprises an oligonucleotide microarray according to the invention and means for comparing a gene expression profile determined by using said microarray with a database of oligodendroglial reference expression profiles. The present invention also comprises kits of parts suitable for performing a method of the invention as well as the use of the various products of the invention, including databases, microarrays, oligonucleotide probes and classification schemes in diagnostic or prognostic methods of the invention.

The present invention discloses a number of genes that are differentially-expressed in oligodendroglial tumor classes. These differentially-expressed genes are shown in Tables 3-7. Many of the treatment sensitivity-associated transcripts (Table 3) are involved in transcriptional regulation, interaction with the extracellular matrix or affect cytoskeletal dynamics. For example genes involved in regulation of transcription include: i) PAX8, a member of the paired box gene family of transcription factors; ii) Sp110, a protein that can function as an activator of transcription; iii) RENT1, a protein involved in mRNA nuclear export and nonsense-mediated mRNA decay; and iv) TNFSF13, a member of the tumor necrosis factor ligand family that activate transcription via e.g. NF-κB. TNFSF13 transgenic mice develop lymphoid tumors (Planelles, L. et al., (2004) Cancer Cell 6:399-408). Transcripts involved in the cellular interaction with the extracellular matrix include: i) MAN1C1, an α-mannosidase involved in the maturation of N-linked glycans; ii) CHSY1, which synthesizes chondroitin sulfate, a widely expressed glycosaminoglycan and iii) LGALS9, a member of the tandem-repeat type galectins that bind beta-galactoside. LGALS9 is expressed at high levels in distant metastasis of breast cancer (for review see (Hirashima, M. et al., (2004) Glycoconj. J. 19:593-600). Also two treatment sensitivity associated transcripts that are involved in regulation of cytoskeletal dynamics were identified: i) ARPC1B, involved in the branching of actin filaments and downregulated in gastric cancers; and ii) IQGAP1, a scaffolding protein that interacts with components of the cytoskeleton. Overexpression of IQGAP1 enhances cell migration (Mataraza, J. M. et al., (2003) J. Biol. Chem. 278: 41237-41245). Other genes expressed at high levels in chemoresistant oligodendroglial tumors include i) AQP1, a water channel often highly expressed in malignant gliomas that plays a role in migration and neovascularization of tumors; ii) TRIM56, a member of the tripartite motif family and iii) ARH, an adaptor protein that interacts with the LDL receptor. In summary, the genes identified in this invention that are associated with treatment sensitivity (Table 3) are involved in several discrete cellular processes and further study on these transcripts may help identify the molecular mechanisms that underlie treatment sensitivity.

Comparison of expression profiles to patient survival after diagnosis identified 103 differentially expressed probesets (Table 4). The observation that many genes are differentially expressed suggests that different molecular pathways are affected in the tumors of short and long survivors. The genetic background of the tumor therefore appears to be an important factor in determining the prognosis of the patient, although other factors also can contribute significantly to patient survival (e.g. tumor location). Therefore, genes that are differentially expressed between long and short survivors can help identify patient subgroups that are associated with favorable prognosis. Functional analysis reveals that many transcripts upregulated in short survivors are involved in the regulation of transcription. Examples include, i) BTEB1, a member of the SP1-like/KLF family of transcription regulators, ii) BCL10, an activator NF-κB, iii) DR1, a transcriptional repressor, iv) JUN, part of the AP1 transcription factor complex, v) PTPN12 and vi) PTP4A2, members of the protein tyrosine phosphatase family that regulate processes including cell growth, differentiation, mitotic cycle, and oncogenic transformation, vii) SFRS4, a member of the SR family of splicing factors, and viii) LMO4, a LIM domain containing protein that may play a role as a transcriptional regulator. In contrast, transcripts encoding proteins involved in RNA translation are downregulated in short survivors. They include five ribosomal proteins (RPL24, RPL3, PRL7, RPLP2 and RPS3) and proteins involved in post-transcriptional modification like CUGBP1 and RBM4.

This invention shows that expression profiling can identify transcripts associated with chromosomal aberrations, therapeutic response and survival after diagnosis in patients suffering from oligodendroglial tumors. As described above this knowledge can be used to identify patient classes with a high likelihood to respond to treatment and patient classes with favorable prognosis.

The following examples are offered by way of illustration and not by way of limitation.

Example Methods Tumor Samples:

Patients were chosen with (anaplastic) oligodendroglioma or mixed oligoastrocytoma with enhancing disease at the time of chemotherapy. Patients were treated in a single institution (Erasmus MC) in clinical trials evaluating the efficacy of Temozolomide or PCV. Only patients with an evaluable for response to chemotherapy were included in this study. Treatment response was evaluated by MRI and scored according to McDonald's criteria (Macdonald D. R. et al., (1990) J. Clin. Oncol. 8:1277-1280). Tumor size was defined as the product of the two largest perpendicular tumor diameters. Complete response (CR) was defined as disappearance of all contrast-enhancing tumor on two subsequent scans at least one month apart, the patient being off steroids and neurologically stable or improved. Partial response (PR) was defined as ≧50% reduction in tumor area on two subsequent scans at least one-month apart, steroids stable or decreased and neurologically stable or improved. Progressive disease (PD) was defined as ≧25% increase in tumor area, new tumor on MRI or neurological deterioration and steroids stable or increased. All other situations were considered stable disease (SD). Samples were collected immediately after surgical resection, snap frozen, and stored at −800 C in the Erasmus MC brain tumor tissue bank. Samples were visually inspected on 10 μm H&E stained frozen sections by the neuropathologist (J.M.K). Samples with less than 80% tumor were omitted from this study. Tissue adjacent to the inspected sections was subsequently used for nucleic acid isolation. Using these criteria, 28 oligodendroglial tumors were selected (Table 1). Four additional tumor samples with insufficient RNA quantity for array analysis were selected for confirmation of differentially expressed genes using QPCR.

Nucleic Acid Isolation:

Tissues were homogenized using a polytron following which RNA and genomic DNA were extracted using Trizol (Life-Technologies) according to the manufacturers instructions. Total RNA, present in the aqueous phase after extraction, was precipitated in isopropanol, redissolved in diethyl-pyrocarbonate treated water and further purified on RNeasy mini columns (Qiagen). Genomic DNA present in the organic phase was precipitated using ethanol, washed in 0.1M Na-citrate, 10% ethanol and dissolved in 8 mM NaOH whereafter the pH was adjusted to 8.4 using 1M Hepes (free acid).

cDNA Synthesis And Array Hybridization

RNA quality was assessed on agarose gel and Bioanalyser (Agilent). cDNA synthesis and cRNA labeling was performed using the alternative protocol for one-cycle cDNA synthesis. Biotin-labeled cRNA was generated using the ENZO Highyield RNA transcript labeling kit (ENZO life sciences inc, NY). Affymetrix (Santa Clara, Calif.) HG U133-plus2 microarrays were hybridized overnight with 15 μg biotin labeled cRNA. 54.675 probesets (a probeset is a set of oligonucleotide probes that examines the expression of a single transcript) are spotted on these arrays allowing expression profiling of virtually all human transcripts. Multiple probesets may be directed against the same transcript. Microarrays were then washed using fluidics stations according to standard Affymetrix protocols.

Microsatellite Analysis

Microsatellites were amplified by PCR on 10 ng genomic DNA using forward and reversed primers and a fluorescently labeled M13 (−21) primer. Primers and cycling conditions are stated in supplementary table 1. PCR products were precipitated, dissolved in formamide and run on an ABI 3100 genetic analyzer (Applied Biosystems). Samples were analyzed using Genescan 3.7 software (Applied Biosystems) and scored by two independent researchers. Since non-neoplastic tissues were not available for most of the tumor samples, allelic losses were statistically determined as described (Harkes I. C., et al. (2003) Br. J. Cancer 89:2289-2292). Allelic loss was assumed when the tumor sample had a homozygous allele pattern for all microsatellites within the locus (P<0.05 for each locus).

Fluorescence In Situ Hybridization

1p/19q status of samples with non-informative microsatellite analysis was determined using Fluorescence In Situ Hybridization (FISH) as previously described (Stege E. M. et al., (2005) Cancer 103:802-809). Locus-specific probes for 1p36 (D1S32), centromere 1 (pUC1.77), 19q13.4 (Bac clone 426G3), and 19p13 (Bac clones 957I1, 153P24, and 959O6) were labeled with either biotin-16-dUTP, digoxigenin-16-dUTP (Roche Diagnostics, Mannheim, Germany) or Spectrum Orange (Vysis Illinois, USA) as previously described (23). Probes were detected using FITC-labeled sheep-anti-digoxigenin (Roche Diagnostics) and/or CY3-labeled avidin (Brunschwig Chemie, Amsterdam, The Netherlands). Nuclei were counterstained with 4′,6-diamidino-2-phenylindole (DAPI). Sixty non-overlapping nuclei were enumerated per hybridization. Ratios were calculated as the number of signals of the marker divided by the number of signals of the reference. Ratio <0.80 were considered allelic loss.

Semi-Quantitative RT-PCR

Semi-quantitative RT-PCR was performed using SYBR Green PCR master mix (Applied Biosystems) according to the manufacturers instructions. Expression levels were evaluated relative to HPRT and PDGB controls. Intron spanning primers were designed against 16 genes (supplementary table 2). All primers had an amplification efficiency >80% (determined by serial dilution) and generated a single amplification product at a temperature above 77° C. (determined by melting point analysis). Cycling was performed on an ABI7700 sequence detection system (Applied Biosystems); cycling conditions are stated in supplementary table 2. Amplification of the EFGR receptor was determined by semi-quantitative PCR using identical conditions as described above. 20 ng genomic DNA was used for each reaction. The amount of product amplified using genomic EGFR primers was compared to the amount of product amplified using primers on different chromosomes lying within the F3 and the FGFR3 loci. Statistical analysis was performed using the Mann Whitney U test (eatworms.swmed.edu/˜leon/stats/utest.cgi), values are ±SEM.

Data Analysis:

Arrays were omitted from the analysis when the number of present calls <35% and when the 5′/3′ ratio of GAPDH controls >3. Probesets that were absent (according to Affymetrix MAS5.0 software) in at least 33 of the 34 microarrays were omitted from further analysis. Raw intensities of the remaining probesets (36875) of each chip were log 2 transformed and normalized using quantile normalization. For each probeset, the geometric mean of the hybridization intensities of all samples was calculated. The level of expression of each probeset was determined relative to this geometric mean and log 2 transformed. The geometric mean of the hybridization signal of all samples was used to ascribe equal weight to gene-expression levels. Unsupervised clustering was performed using Omniviz version 3.6.0 (Omniviz, Maynard, Mass.) software. Probesets whose expression levels differed more than 2 fold from the geometric mean in at least one sample were selected for the unsupervised clustering analysis. Similarities between samples is plotted using Omniviz software as Pearson's correlations.

Differentially expressed genes were identified using statistical analysis of microarrays (SAM analysis) (Tusher V. G. et al., Proc. Natl. Acad. Sci. U.S.A. 98:5116-5121). Such supervised analysis correlates gene expression with an external variable. SAM calculates a score for each probeset on the basis of the change in expression relative to the SD of all measurements. Unless otherwise indicated, analyses were performed using stringent statistical parameters with a false discovery rate (FDR) of less than 1 probeset. Differentially expressed probesets were imported into Spotfire DecisionSite (Spotfire, Somerville, Mass.) to perform principle components analysis (PCA) and hierarchical clustering. Data were log 2 transformed followed by calculation of the z-score for each probeset. PCA structures a dataset using as few variables as possible and is a mathematical way to reduce data dimensionality. PCA summarizes the most important variance in a dataset as principle components. For more information on the use of PCA in microarray analysis microarrays see (Raychaudhuri S. et al. (2000), In: Hunter L, Altman B, Dunker A K, Klein T E, Lauderdale K, editors. Pacific Symposium on Biocomputing 1999. Honolulu, Hi.: World Scientific Press; 2000) and references therein. Hierarchical clustering groups data based on their similarities in gene expression profiles. Weighted average was used to perform most clustering analysis, in which the distance between two clusters is defined as the average of distances between all pairs of objects. Unlike clustering based on unweighted averages, the weighted average ascribes equal weight to the two branches of the dendrogram that are about to be fused. Ward's hierarchical clustering method forms groups in a manner that minimizes the loss associated with each grouping. At each step in this analysis, the two clusters whose fusion results in minimum increase in information loss are combined.

Results Samples:

Patient data, histological diagnosis, chromosomal aberrations, and response to chemotherapy are summarized in table 1. In total we performed expression analysis on 28 oligodendroglial tumors (2 lowgrade and 26 anaplastic oligodendrogliomas), and 6 control brain samples (4 samples from whole cortex, 2 from white matter only). We identified 14/28 samples (50%) with loss of most/all of the short arm of chromosome 1 (sample 18 had a predicted loss distal to 1p33) and 16/28 (57%) samples with loss of 19q (see Table 1). Most tumors showed combined loss or retention of 1p and 19q: only three tumors showed loss of 19q without loss of 1p, one showed LOH on 1p35.2 without loss of 19q. EGFR amplification and LOH on 10q was identified in 4/28 (14%) oligodendroglial tumors, three of which showed combined EGFR amplification and 10q LOH. When comparing the response rate (CR+PR vs. PD+SD) to loss of the telomeric end of chromosome 1, a response to chemotherapy was observed in 12/14 (86%) samples with 1p35.2 LOH and 6/14 (43%) without loss of 1p35.2. Similar results were obtained when comparing the response rate to LOH on 19q or to combined LOH on 1p and 19q (table 1). All four tumors in which the EGFR genomic region was amplified had retained both copies of 1p and 19q and showed no response to chemotherapy (progressive disease for all). 3/4 tumors with 10q LOH showed no response to treatment.

Unsupervised Clustering:

Unsupervised clustering identifies a number of subgroups, summarized in FIG. 1. A first subgroup consists mainly of control samples but also includes low-grade tumor samples. Because the amount of tumor present in all samples was high (determined by visual inspection of sections prior to the sample used for expression profiling), this close homology to control brain tissue is likely to reflect an intrinsic property of low-grade oligodendroglial tumors. The low-grade oligodendroglioma samples have a higher homology to samples from whole cortex than to samples from white matter. Group II consists of tumor samples that have LOH on 1p and 19q and has a relatively good prognosis: All but one sample respond favorably to chemotherapy and most (4/6) patients with CR are found in this group. Patients in this group also have a relatively long survival both after diagnosis (15.3±3.6 years) and after surgical resection of the tumor (4.8±1.5 years). Group III has the worst prognosis: None of the tumors respond to chemotherapy, the average time of survival after diagnosis was short (1.9±0.2 years) as was the average time after surgical resection (1.5±0.3 years). All tumors of this subgroup have retained both copies of 1p and 19q and are characterized by an amplification of the EGFR locus. The samples between groups II and III have a more mixed appearance, there is some degree of correlation with both groups I and group III. Many samples with PR and all samples with SD are found in this group. Survival after diagnosis and surgical resection is intermediate between groups II and III: 8.3±1.5 and 2.3±0.3 years respectively.

Supervised Clustering: Tumor Vs. Controls

We first performed supervised clustering to identify genes that are differentially expressed between control and tumors tissue. SAM analysis identified 1881 differentially expressed probesets (˜1413 genes). Strongest downregulated transcripts in oligodendroglial tumors include those that encode proteins expressed in mature oligodendrocytes: myelin associated oligodendrocyte basic protein (MOBP), myelin oligodendrocyte glycoprotein (MOG), myelin associated glycoprotein (LAG), claudin 11 (CLDN11) and myelin basic protein (MBP). These transcripts are expressed (±SD) at 0.052±0.021 (4 probesets), 0.10±0.013 (4 probesets), 0.086 (1 probeset), 0.30±0.25 (2 probesets), and 0.21±0.17 (7 probesets) levels of control brain mRNA respectively. This downregulation was observed in each sample. The strong downregulation in low-grade samples confirms the hypothesis that their homology to control brain tissue (see FIG. 1) is a result of the genes expressed by the tumor. The downregulation of MOG was confirmed using RT-PCR (table 2).

It has been reported that PDGFRα is often highly expressed in oligodendroglial tumors (Riemenschneider M. J. et al., (2004) Acta Neuropathol. (Berlin) 107:277-282). However, this gene was not present in the set of tumor-associated genes identified by our screen. Closer inspection reveals that, although PDGFRα is on average upregulated 4.1 fold, the high variation of upregulation (4.1±4.7) indicates that this transcript is not a reliable marker for the amount of tumor present in the sample. In fact, we failed to observe any upregulation in 10/28 samples. The select upregulation of PDGFRα in a subset of samples was confirmed using RTPCR.

Supervised Clustering on Chromosomal Aberrations

Supervised clustering was performed to identify genes associated with specific chromosomal losses. For this we compared expression profiles of samples with i) 1p LOH (n=9) vs. no loss (n=9), ii) 19q LOH (n=11) vs. no loss (n=7), and iii) combined 1p and 19q LOH (n=6) with no loss on either arm (n=6). SAM analysis identified 376, 64 and 60 probesets as being differentially expressed following loss of 1p, 19q or 1p and 19q respectively. Probesets are listed in supplementary table 3. Interestingly, many of the identified probesets are located on the lost chromosomal arm(s): 136/376 (36.1%) probesets are located on 1p, 25/64 (39.1%) on 19q and 49/60 (82%) on 1p or 19q. Of the differentially expressed genes located on the lost chromosomal arm(s), the ratio (═SD) loss vs. no loss is 0.53±0.22 (1p), 0.54±0.07 (19q) and 0.53±0.09 (1p and 19q) indicating that loss of one allele reduces expression levels by ˜50%. In fact, all but two of the differentially expressed probesets that are located on the lost chromosomal(s) are downregulated. This correlation between chromosomal loss and expression level therefore suggest that these genes have an allele-number dependent expression level. Furthermore, the differentially expressed genes can be identified across the entire chromosomal arms and suggests the entire arms have been lost.

Principle components analysis (PCA) and hierarchical clustering of genes associated with LOH on 1p and 19q is depicted in FIG. 2. All anaplastic oligodendrogliomas with combined loss/retention of 1p and 19q were correctly distributed by the first principal component axis, PCA1. This correct distribution includes 7 samples (2 samples that have retained both 1p and 19q copies and 5 samples with LOH on 1p and 19q) that were omitted from the clustering analysis. Further confirmation of a subset of differentially expressed genes by RT-PCR is shown in table 2 (including 4 additional oligodendroglial tumors).

Genes Associated with Chemosensitivity

We next performed supervised clustering to identify genes that are associated with response to chemotherapy. For this analysis we compared mRNA expression levels between tumors that show a response to chemotherapy (CR+PR), and those that do not (SD+PD). Such comparison using SAM (FDR<1 gene) identified 16 differentially expressed probesets that are listed in the supplementary table 3. 160 differentially expressed probesets (137 genes) were identified using less stringent statistical analysis (FDR=4.9%), of which 31 (27 genes) are located on chromosomes 1p or 19q (19%). Confirmation of differentially expressed genes was performed using RT-PCR on IQGAP, MAN1C1, TRIM56 and AQP1 transcripts (table 2).

PCA based on the 16 genes associated with chemotherapeutic response identifies three main subgroups (FIG. 3): Samples with no response to chemotherapy (SD and PD, red), samples with response to treatment (CR and PR, green), and control samples (gray). Similarly, hierarchical clustering also separates the majority of oligodendroglial tumors with response to chemotherapy from those that show no or little response to treatment (FIG. 3). Similar results were obtained when clustering was performed on 160 differentially expressed probesets identified using FDR=4.9%. Most oligodendroglial tumors were correctly distributed on their response to treatment by the first principal component axis, PCA1: PCA1>0 in 14/18 samples that respond to treatment whereas PCA1<0 in 10/10 samples with no response to treatment. Only 4/28 samples were therefore incorrectly classified based on expression of genes associated with chemosensitivity. In comparison, 8/28 samples are incorrectly classified when predicting response to treatment based on the 1p chromosomal status: 6/14 tumors without LOH on 1p show response to treatment and 2/14 with LOH on 1p do not respond to treatment.

Genes Associated with Survival

We next performed supervised clustering to identify genes associated with overall survival after diagnosis. For this analysis we compared expression profiles of tumors from patients with the shortest survival time (2.0±0.3 years, n=7) with those with the longest survival time (17.6±4.4 years, n=8) after diagnosis. SAM analysis identified 103 probesets (92 genes, see supplementary data) associated with patient survival. 30 (29%) of these probesets are located on either 1p or 19q chromosomal arms. PCA of survival-associated genes identifies three main clusters of samples: oligodendroglial tumors with short survival, oligodendroglial tumors with long survival and control samples. Low-grade samples cluster between control and tumor samples. Similar subgroups were identified by hierarchical clustering using these probesets (FIG. 4). It is interesting to note that the subgroups identified by hierarchical clustering are virtually identical to the subgroups that were identified by unsupervised clustering (FIG. 1). Most oligodendroglial tumors were correctly distributed on survival after diagnosis by the first principal component axis, PCA1: PCA1>0 in 12/14 samples with favorable prognosis (i.e. survival time >7 years after diagnosis) whereas PCA1<0 in 8/11 samples with relatively short survival after diagnosis (i.e. <7 years).

TABLE 1 Summary of patient data, histological diagnosis and response to chemotherapy of samples used in this study. sample 1p 19q 10q EGFR surv Sample sex age type status status status ampl Response ther surv tot op alive 1 F 39 control no 3 F control no 4 M 63 control no 7 M 63 control no 8 F 45 AOD LOH LOH no no CR PCV 15 8.5 yes LOH 9 M 35 AOD LOH LOH no no PR temo 13 2.7 no LOH 10 M 59 AOD LOH LOH no no PR temo 9.8 1.5 no LOH 11 M 44 AOD LOH LOH no no PR PCV 12 3.2 no LOH 12 F 57 AOD no LOH no no PR PCV 19 1.9 no LOH LOH 13 M 40 AOD LOH LOH no no PR PCV 24 1.9 no LOH 14 M 59 AOD no no LOH yes PD PCV 2 1.6 no LOH LOH 15 F 19 AOD no no no no CR temo 3.7 3.7 no LOH LOH LOH 16 M 49 AOA no LOH no no SD PCV 10.9 1.2 no LOH LOH 17 M 47 AOD no no no no PD PCV 4 3.9 no LOH LOH LOH 18 M 34 AOD LOH no no no PR PCV 1.8 0.4 no LOH LOH 20 M 50 AOD LOH LOH no no SD temo 11 1.3 no LOH 21 M 32 AOD LOH LOH no no CR PCV 3.9 3.6 yes LOH 22 M 55 AOD no no LOH yes PD PCV 1.5 1.4 no LOH LOH 23 F 45 AOD LOH LOH no no PR PCV 19 6.1 no LOH 24 M 43 AOD no no no no PR PCV 11 1.0 no LOH LOH LOH 25 M 51 AOD LOH LOH no no PD temo 10 3.0 no LOH 28 M 35 AOD LOH LOH no no CR PCV 2.2 2.2 yes LOH 29 M 52 AOD no no LOH yes PD temo 2.3 2.1 no LOH LOH 30 M 88 control no 31 F 68 control no 34 M 45 AOD no no no yes PD PCV 1.8 1.0 no LOH LOH LOH 36 F 21 AOA no LOH no no PR temo 2.5 2.4 no LOH LOH 37 F 33 AOD LOH LOH no no CR PCV 23 11.1 no LOH 38 F 39 OD LOH LOH no no CR PCV 9.7 6.6 no LOH 40 M 45 AOD LOH LOH no no PR PCV 16 3.5 no LOH 41 F 39 AOA no no LOH no PR PCV 4.8 4.1 no LOH LOH 42 F 37 OD no no no no PR PCV 8 8.0 yes LOH LOH LOH 44 M 39 AOD no no no no SD temo 2.7 2.7 no LOH LOH LOH 46 M 30 AOD no no no no SD PCV 6.3 2.5 no LOH LOH LOH Additional samples used for RT-PCR confirmation 26 M 52 OD LOH no no no MR PCV yes loss loss 27 M 44 AOD no LOH loss no no stopped PCV yes loss 32 M 72 control no 33 M 49 AOD LOH loss no no PR PCV yes loss 45 AOD no LOH no no no unknown loss loss M: male; F: female; ctr: normal brain; ctr/w: control brain white matter; OD oligodendroglioma (grade II); AOD: anaplastic oligodendroglioma, AOA anaplastic oligoastrocytoma; LOH: loss of heterozygosity; ampl: amplification of the EGFR locus; ther.: therapy: PCV: combination therapy of procarbazine, CCNU, and vincristine; temo: temozolomide. Treatment response was scored according to McDonald's criteria (20) CR: complete response; PR: partial response; SD: stable disease; PD: progressive disease. Surv tot: patient survival after diagnosis (years); Surv op: patient survival after surgical resection of the sample used in this study.

TABLE 2 Confirmation of a subset of differentially expressed genes identified by expression profiling. Differential expression of most transcripts was reconfirmed by RT-PCR. The relative expression levels between control (either no loss of 1p, 19q, no tumor or CR/PR) and test set (either LOH on 1p, 19q, tumor or SD/PD) also remained similar on the array (rel expr array) and by RT-PCR (rel expr QPCR). marker rel expr rel expr QPCR QPCR gene for array QPCR ctr marker P F3 1p LOH 5.4 6.9 0.52 ± 0.21 3.63 ± 2.88 p < 0.001 IQGAP 1p LOH 2.8 4.6 0.48 ± 0.15 2.19 ± 1.09 p < 0.001 PPAP2B 1p LOH 3.3 4.4 2.38 ± 0.75 10.4 ± 8.1  p < 0.005 GNG12 1p LOH 2.8 5.4 0.61 ± 0.23 3.28 ± 1.19 p < 0.001 MOG tumor 11.6 21.9 2.44 ± 0.84 53.4 ± 5.0  p < 0.00001 LANCL2 EGFR 9.6 15.7 4.84 ± 0.56 76.1 ± 25.6 p < 0.005 ampl EGFR EGFR 6.3 14.4 33.3 ± 4.6  480 ± 112 p < 0.005 ampl CASP3 19q 2.0 1.7 2.57 ± 0.83 4.47 ± 1.41 ns LOH ZNF222 19q 2.4 1.6 0.34 ± 0.10 0.54 ± 0.17 ns LOH DCDT 19q 4.0 4.8 0.65 ± 0.29 3.14 ± 0.79 p < 0.005 LOH MAN1C1 response 3.5 3.0 2.09 ± 0.50 6.24 ± 1.51 p < 0.05 IQGAP1 response 2.4 2.3 0.99 ± 0.41 2.32 ± 1.28 p < 0.05 TRIM56 response 2.3 2.7 0.17 ± 0.05 0.47 ± 0.21 p < 0.05 AQP1 response 9.7 7.5 2.42 ± 1.21 18.2 ± 13.2 p < 0.02 QPCR ctr: expression of the examined transcript in control samples (either no loss of 1p, 19q, no tumor or CR/PR) relative to PDGB expression levels; QPCR marker: expression of the examined transcript in test samples (either LOH on 1p, 19q, no tumor or CR/PR) relative to PDGB expression levels. Statistical analysis was performed on QPCR ctr vs. marker using the Mann Whitney U test (two tailed), values are ±SE.

TABLE 3 Differentially expressed probesets, which are able to discriminate on basis of response tot treatment Probe Set ID Title Gene Symbol Location 1552506_at hypothetical protein FLJ38464 Chr: 9q34.11 FLJ38464 1554830_a_at dudulin 2 TSAP6 Chr: 2q14.2 1555600_s_at apolipoprotein L, 4 APOL4 Chr: 22q11.2-q13.2 1555852_at transporter 1, ATP- TAP1 Chr: 6p21.3 binding cassette, sub- family B (MDR/TAP) 1555997_s_at insulin-like growth factor IGFBP5 Chr: 2q33-q36 binding protein 5 1556643_at hypothetical protein LOC93343 Chr: 19p13.12 BC011840 1567628_at CD74 antigen (invariant CD74 Chr: 5q32 polypeptide of major histocompatibility complex, class II antigen-associated) 1568619_s_at hypothetical protein LOC162073 Chr: 16p13.11 LOC162073 200660_at S100 calcium binding S100A11 Chr: 1q21 protein A11 (calgizzarin) 200673_at lysosomal-associated LAPTM4A Chr: 2p24.3 protein transmembrane 4 alpha 200791_s_at IQ motif containing IQGAP1 Chr: 15q26.1 GTPase activating protein 1 200867_at zinc finger protein 313 ZNF313 Chr: 20q13.13 200887_s_at signal transducer and STAT1 Chr: 2q32.2 activator of transcription 1, 91 kDa 201053_s_at proteasome (prosome, PSMF1 Chr: 20p13 macropain) inhibitor subunit 1 (PI31) 201125_s_at integrin, beta 5 ITGB5 Chr: 3q21.2 201136_at proteolipid protein 2 PLP2 Chr: Xp11.23 (colonic epithelium- enriched) 201259_s_at synaptophysin-like SYPL Chr: 7q22.2 protein 201319_at myosin regulatory light MRCL3 Chr: 18p11.31 chain MRCL3 201324_at epithelial membrane EMP1 Chr: 12p12.3 protein 1 201325_s_at epithelial membrane EMP1 Chr: 12p12.3 protein 1 201336_at vesicle-associated VAMP3 Chr: 1p36.23 membrane protein 3 (cellubrevin) 201339_s_at sterol carrier protein 2 SCP2 Chr: 1p32 201464_x_at v-jun sarcoma virus 17 JUN Chr: 1p32-p31 oncogene homolog (avian) 201465_s_at v-jun sarcoma virus 17 JUN Chr: 1p32-p31 oncogene homolog (avian) 201531_at zinc finger protein 36, ZFP36 Chr: 19q13.1 C3H type, homolog (mouse) 201560_at chloride intracellular CLIC4 Chr: 1p36.11 channel 4 201590_x_at annexin A2 ANXA2 Chr: 15q21-q22 201817_at ubiquitin-protein KIAA0010 Chr: 7q36.3 isopeptide ligase (E3) 201887_at interleukin 13 receptor, IL13RA1 Chr: Xq24 alpha 1 201954_at actin related protein 2/3 ARPC1B Chr: 7q22.1 complex, subunit 1B, 41 kDa 201963_at fatty-acid-Coenzyme A FACL2 Chr: 4q34-q35 ligase, long-chain 2 202096_s_at benzodiazapine receptor BZRP Chr: 22q13.31 (peripheral) 202132_at transcriptional co- TAZ Chr: 3q23-q24 activator with PDZ- binding motif (TAZ) 202133_at transcriptional co- TAZ Chr: 3q23-q24 activator with PDZ- binding motif (TAZ) 202193_at LIM domain kinase 2 LIMK2 Chr: 22q12.2 202377_at leptin receptor LEPR Chr: 1p31 202803_s_at integrin, beta 2 (antigen ITGB2 Chr: 21q22.3 CD18 (p95), lymphocyte function-associated antigen 1; macrophage antigen 1 (mac-1) beta subunit) 202863_at nuclear antigen Sp100 SP100 Chr: 2q37.1 203044_at carbohydrate CHSY1 Chr: 15q26.3 (chondroitin) synthase 1 203132_at retinoblastoma 1 RB1 Chr: 13q14.2 (including osteosarcoma) 203153_at interferon-induced IFIT1 Chr: 10q25-q26 protein with tetratricopeptide repeats 1 203236_s_at lectin, galactoside- LGALS9 Chr: 17q11.2 binding, soluble, 9 (galectin 9) 203275_at interferon regulatory IRF2 Chr: 4q34.1-q35.1 factor 2 203379_at ribosomal protein S6 RPS6KA1 Chr: 3 kinase, 90 kDa, polypeptide 1 203426_s_at insulin-like growth factor IGFBP5 Chr: 2q33-q36 binding protein 5 203567_s_at tripartite motif-containing TRIM38 Chr: 6p21.3 38 203735_x_at Homo sapiens — — transcribed sequence with weak similarity to protein ref: NP_060312.1 (H. sapiens) hypothetical protein FLJ20489 [Homo sapiens] 203879_at phosphoinositide-3- PIK3CD Chr: 1p36.2 kinase, catalytic, delta polypeptide 203973_s_at KIAA0146 protein KIAA0146 Chr: 8q11.21 204017_at KDEL (Lys-Asp-Glu-Leu) KDELR3 Chr: 22q13.1 endoplasmic reticulum protein retention receptor 3 206515_at cytochrome P450, family CYP4F3 Chr: 19p13.2 4, subfamily F, polypeptide 3 207542_s_at aquaporin 1 (channel- AQP1 Chr: 7p14 forming integral protein, 28 kDa) 207753_at zinc finger protein 304 ZNF304 Chr: 19q13.4 208540_x_at — — — 208789_at polymerase I and PTRF Chr: 17q21.31 transcript release factor 208966_x_at interferon, gamma- IFI16 Chr: 1q22 inducible protein 16 209047_at aquaporin 1 (channel- AQP1 Chr: 7p14 forming integral protein, 28 kDa) 209091_s_at SH3-domain GRB2-like SH3GLB1 Chr: 1p22 endophilin B1 209619_at CD74 antigen (invariant CD74 Chr: 5q32 polypeptide of major histocompatibility complex, class II antigen-associated) 209762_x_at SP110 nuclear body SP110 Chr: 2q37.1 protein 209823_x_at major histocompatibility HLA-DQB1 Chr: 6p21.3 complex, class II, DQ beta 1 209949_at neutrophil cytosolic NCF2 Chr: 1q25 factor 2 (65 kDa, chronic granulomatous disease, autosomal 2) 209969_s_at signal transducer and STAT1 Chr: 2q32.2 activator of transcription 1, 91 kDa 210426_x_at RAR-related orphan RORA Chr: 15q21-q22 receptor A 210427_x_at annexin A2 ANXA2 Chr: 15q21-q22 210582_s_at LIM domain kinase 2 LIMK2 Chr: 22q12.2 210829_s_at single-stranded DNA SSBP2 Chr: 5q14.1 binding protein 2 210840_s_at IQ motif containing IQGAP1 Chr: 15q26.1 GTPase activating protein 1 211168_s_at regulator of nonsense RENT1 Chr: 19p13.2-p13.11 transcripts 1 211366_x_at caspase 1, apoptosis- CASP1 Chr: 11q23 related cysteine protease (interleukin 1, beta, convertase) 211429_s_at serine (or cysteine) SERPINA1 Chr: 14q32.1 proteinase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 1 211495_x_at tumor necrosis factor TNFSF13 Chr: 17p13.1 (ligand) superfamily, member 13 211561_x_at mitogen-activated protein MAPK14 Chr: 6p21.3-p21.2 kinase 14 211612_s_at interleukin 13 receptor, IL13RA1 Chr: Xq24 alpha 1 211656_x_at major histocompatibility HLA-DQB1 Chr: 6p21.3 complex, class II, DQ beta 1 211733_x_at sterol carrier protein 2 SCP2 Chr: 1p32 211749_s_at vesicle-associated VAMP3 Chr: 1p36.23 membrane protein 3 (cellubrevin) 211924_s_at plasminogen activator, PLAUR Chr: 19q13 urokinase receptor 211959_at insulin-like growth factor IGFBP5 Chr: 2q33-q36 binding protein 5 212203_x_at interferon induced IFITM3 Chr: 11p15.5 transmembrane protein 3 (1-8U) 212268_at serine (or cysteine) SERPINB1 Chr: 6p25 proteinase inhibitor, clade B (ovalbumin), member 1 212687_at LIM and senescent cell LIMS1 Chr: 2q12.3 antigen-like domains 1 212859_x_at metallothionein 1E MT1E Chr: 16q13 (functional) 213293_s_at tripartite motif-containing TRIM22 Chr: 11p15 22 213446_s_at IQ motif containing IQGAP1 Chr: 15q26.1 GTPase activating protein 1 213503_x_at annexin A2 ANXA2 Chr: 15q21-q22 213504_at COP9 subunit 6 (MOV34 COPS6 Chr: 7q22.1 homolog, 34 kD) 213698_at zinc finger protein 258 ZNF258 Chr: 1p34.2 214087_s_at myosin binding protein MYBPC1 Chr: 12q23.3 C, slow type 214180_at Homo sapiens — — transcribed sequence with weak similarity to protein ref: NP_060265.1 (H. sapiens) hypothetical protein FLJ20378 [Homo sapiens] 214257_s_at hypothetical protein FLJ21272 Chr: 1q21.2 FLJ21272 214684_at MADS box transcription MEF2A Chr: 15q26 enhancer factor 2, polypeptide A (myocyte enhancer factor 2A) 214791_at hypothetical protein LOC93349 Chr: 2q37.1 BC004921 216526_x_at major histocompatibility HLA-C Chr: 6p21.3 complex, class I, C 216598_s_at chemokine (C-C motif) CCL2 Chr: 17q11.2-q21.1 ligand 2 217388_s_at kynureninase (L- KYNU Chr: 2q22.3 kynurenine hydrolase) 217730_at PP1201 protein PP1201 Chr: 2p24.3-p24.1 217746_s_at programmed cell death 6 PDCD6IP Chr: 3p22.3 interacting protein 217788_s_at UDP-N-acetyl-alpha-D- GALNT2 Chr: 1q41-q42 galactosamine:polypeptide N- acetylgalactosaminyltransferase 2 (GalNAc-T2) 218154_at hypothetical protein FLJ12150 Chr: 8q24.3 FLJ12150 218162_at HNOEL-iso protein HNOEL-iso Chr: 1p13.1 218247_s_at hypothetical protein LOC51320 Chr: 18q21.1 LOC51320 218418_s_at KIAA1518 protein KIAA1518 Chr: 19p13.2 218673_s_at ubiquitin activating GSA7 Chr: 3p25.2 enzyme E1-like protein 218802_at hypothetical protein FLJ20647 Chr: 4q25 FLJ20647 218918_at mannosidase, alpha, MAN1C1 Chr: 1p35 class 1C, member 1 218943_s_at DEAD/H (Asp-Glu-Ala- RIG-I Chr: 9p12 Asp/His) box polypeptide 219505_at cat eye syndrome CECR1 Chr: 22q11.2 chromosome region, candidate 1 219706_at chromosome 20 open C20orf29 Chr: 20p13 reading frame 29 219751_at hypothetical protein FLJ21148 Chr: 16q13 FLJ21148 220088_at complement component C5R1 Chr: 19q13.3-q13.4 5 receptor 1 (C5a ligand) 220407_s_at transforming growth TGFB2 Chr: 1q41 factor, beta 2 220477_s_at chromosome 20 open C20orf30 Chr: 20p13 reading frame 30 221773_at ELK3, ETS-domain ELK3 Chr: 12q23 protein (SRF accessory protein 2) 221790_s_at LDL receptor adaptor ARH Chr: 1p36-p35 protein 222448_s_at UMP-CMP kinase UMP-CMPK — 223047_at chemokine-like factor CKLFSF6 Chr: 3p22.3 super family 6 223165_s_at inositol hexaphosphate IHPK2 Chr: 3p21.31 kinase 2 223376_s_at brain protein I3 BRI3 Chr: 7q22.1 223642_at Zic family member 2 ZIC2 Chr: 13q32 (odd-paired homolog, Drosophila) 223681_s_at InaD-like protein INADL Chr: 1p32.1 224584_at chromosome 20 open C20orf30 Chr: 20p13 reading frame 30 224840_at FK506 binding protein 5 FKBP5 Chr: 6p21.3-21.2 224856_at FK506 binding protein 5 FKBP5 Chr: 6p21.3-21.2 225267_at karyopherin alpha 4 KPNA4 Chr: 3q25.33 (importin alpha 3) 225415_at rhysin 2 LOC151636 Chr: 3q21.1 225869_s_at unc-93 homolog B1 (C. elegans) UNC93B1 Chr: 11q13 226040_at Homo sapiens cDNA — — FLJ11958 fis, clone HEMBB1000996. 226074_at hypothetical protein FLJ32332 Chr: 3p21.31 FLJ32332 226621_at fibrinogen, gamma FGG Chr: 4q28 polypeptide 226628_at THO complex 2 THOC2 Chr: Xq25-q26.3 226694_at A kinase (PRKA) anchor AKAP2 Chr: 9q31-q33 protein 2 227013_at LATS, large tumor LATS2 Chr: 13q11-q12 suppressor, homolog 2 (Drosophila) 227066_at similar to MOB-LAK LOC148932 Chr: 1p34.1 227474_at paired box gene 8 PAX8 Chr: 2q12-q14 227792_at Homo sapiens cDNA: — — FLJ22994 fis, clone KAT11918. 227801_at tumor suppressor TSBF1 TSBF1 Chr: 3q26.1 227837_at hypothetical protein FLJ20309 Chr: 2q33.3 FLJ20309 227882_at fukutin-related protein FKRP Chr: 19q13.33 228042_at ADP-ribosylarginine ADPRH Chr: 3q13.31-q13.33 hydrolase 228229_at KIAA1951 protein KIAA1951 Chr: 19q13.31 228369_at trinucleotide repeat TNRC5 Chr: 6pter-p12.1 containing 5 228410_at GRB2-associated GAB3 Chr: Xq28 binding protein 3 228425_at Homo sapiens, clone — — IMAGE: 4820851, mRNA 228651_at hypothetical gene Chr: 1 supported by AK075366 228949_at putative NFkB activating FLJ23091 Chr: 1p31.2 protein 373 228980_at hypothetical gene Chr: 17q21.1 supported by AK091492; AL831912 229101_at hypothetical protein LOC150166 Chr: 22q11.21 LOC150166 229143_at CCR4-NOT transcription CNOT3 Chr: 19q13.4 complex, subunit 3 229812_at ubiquitin specific USP31 Chr: 1p36.12 protease 31 230636_s_at basic transcription BTEB1 Chr: 9q13 element binding protein 1 231876_at tripartite motif-containing TRIM56 Chr: 7q22.1 56 233103_at Homo sapiens cDNA — — FLJ14109 fis, clone MAMMA1001322, moderately similar to B- CELL GROWTH FACTOR PRECURSOR. 240277_at solute carrier family 30 SLC30A7 Chr: 1p21.2 (zinc transporter), member 7 240656_at Homo sapiens — — transcribed sequences 242521_at Homo sapiens, similar to — — Alu subfamily SQ sequence contamination warning entry, clone IMAGE: 4342162, mRNA 40524_at protein tyrosine PTPN21 Chr: 14q31.3 phosphatase, non- receptor type 21 57163_at elongation of very long ELOVL1 Chr: 1p34.1 chain fatty acids (FEN1/Elo2, SUR4/Elo3, yeast)-like 1 AFFX- — — — HUMISGF3A/M97935_3_at AFFX- — — — HUMISGF3A/M97935_MB_at

TABLE 4 Differentially expressed probesets, which are able to discriminate on basis of patient survival ratio Probe Set ID Title Gene Symbol Location short/long 200902_at 15 kDa selenoprotein SEP15 Chr: 1p31 1.92 231057_at Myotubularin related protein 2 MTMR2 Chr: 11q21 0.38 232929_at Homo sapiens cDNA FLJ13240 — Chr: 3q13.31 0.40 fis, clone OVARC1000496. 213156_at Homo sapiens, clone IMAGE: 4214654 Chr: 3q13.31 0.44 IMAGE: 4214654, mRNA 227082_at Homo sapiens mRNA; cDNA — Chr: 3q13.31 0.39 DKFZp586K1922 (from clone DKFZp586K1922) 227121_at Homo sapiens mRNA; cDNA — Chr: 3q13.31 0.43 DKFZp586K1922 (from clone DKFZp586K1922) 239545_at O-acetyltransferase CAS1 Chr: 7q21.3 0.47 229624_at similar to OPA3 protein; Optic LOC401922 Chr: 19q13.32 1.96 atrophy 3 (Iraqi-Jewish optic atrophy plus) 235384_at similar to RP2 protein, LOC390916 Chr: 19q13.11 2.37 testosterone-regulated - ricefield mouse (Mus caroli) 229075_at Homo sapiens transcribed — Chr: 4q28.1 1.61 sequences 237803_x_at Homo sapiens transcribed — 0.34 sequences 241435_at V-ets erythroblastosis virus E26 ETS1 Chr: 11q23.3 0.36 oncogene homolog 1 (avian) 240216_at CDNA FLJ25794 fis, clone — Chr: 3q13.31 0.42 TST07014 239577_at Homo sapiens, clone — — 0.42 IMAGE: 4182817, mRNA 226189_at Homo sapiens, clone IMAGE: 4794726 Chr: 7p21.1 2.38 IMAGE: 4794726, mRNA 218694_at ALEX1 protein ALEX1 Chr: Xq21.33-q22.2 0.66 226291_at amyotrophic lateral sclerosis 2 ALS2 Chr: 2q33.2 0.78 (juvenile) 223251_s_at ankyrin repeat domain 10 ANKRD10 Chr: 13q34 0.42 224810_s_at ankyrin repeat domain 13 ANKRD13 Chr: 12q24.12 0.65 200782_at annexin A5 ANXA5 Chr: 4q28-q32 2.92 205711_x_at ATP synthase, H+ transporting, ATP5C1 Chr: 10q22-q23 0.69 mitochondrial F1 complex, gamma polypeptide 1 208870_x_at ATP synthase, H+ transporting, ATP5C1 Chr: 10q22-q23 0.68 mitochondrial F1 complex, gamma polypetide 1 205263_at B-cell CLL/lymphoma 10 BCL10 Chr: 1p22 1.75 203543_s_at basic transcription element BTEB1 Chr: 9q13 2.66 binding protein 1 217928_s_at chromosome 11 open reading C11orf23 Chr: 11q13 0.57 frame 23 218796_at chromosome 20 open reading C20orf42 Chr: 20p12.3 0.09 frame 42 217752_s_at cytosolic nonspecific dipeptidase CN2 Chr: 18q22.3 1.59 (EC 3.4.13.18) 222409_at coronin, actin binding protein, 1C CORO1C Chr: 12q24.1 0.52 204264_at carnitine palmitoyltransferase II CPT2 Chr: 1p32 1.59 209489_at CUG triplet repeat, RNA binding CUGBP1 Chr: 11p11 0.67 protein 1 225434_at death effector domain-containing DEDD2 Chr: 19q13.31 2.33 DNA binding protein 2 212131_at DKFZP434D1335 protein DKFZP434D1335 Chr: 19q13.12 1.99 224436_s_at DKFZp564D177 protein DKFZp564D177 Chr: 9q31.2 3.49 201681_s_at discs, large (Drosophila) DLG5 Chr: 10q23 0.46 homolog 5 209187_at down-regulator of transcription 1, DR1 Chr: 1p22.1 1.93 TBP-binding (negative cofactor 2) 204363_at coagulation factor III F3 Chr: 1p22-p21 5.40 (thromboplastin, tissue factor) 209004_s_at F-box and leucine-rich repeat FBXL5 Chr: 4p15.33 1.59 protein 5 208933_s_at hypothetical protein FLJ10359 FLJ10359 Chr: 1q42.3 2.98 240239_at hypothetical protein FLJ14779 FLJ14779 Chr: 19q13.13 1.64 221518_s_at hypothetical protein FLJ20727 FLJ20727 Chr: 11p15.3 0.59 228950_s_at putative NFkB activating protein FLJ23091 Chr: 1p31.2 3.13 373 212558_at ganglioside-induced GDAP1L1 Chr: 20q12 2.80 differentiation-associated protein 1-like 1 201864_at GDP dissociation inhibitor 1 GDI1 Chr: Xq28 0.60 238119_at GL004 protein GL004 Chr: 2q36.3 0.50 212294_at guanine nucleotide binding GNG12 Chr: 1p31.2 4.08 protein (G protein), gamma 12 207157_s_at guanine nucleotide binding GNG5 Chr: 1p22 2.77 protein (G protein), gamma 5 212211_at gene trap ankyrin repeat GTAR Chr: 4q21.1-q21.21 1.43 225784_s_at hepatocellular carcinoma- HCA127 Chr: Xq11.2 0.31 associated antigen 127 223042_s_at hepatitis C virus core-binding HCBP6 Chr: Xq28 0.66 protein 6 219288_at HT021 HT021 Chr: 3p21.1 3.24 209185_s_at insulin receptor substrate 2 IRS2 Chr: 13q34 2.40 201464_x_at v-jun sarcoma virus 17 oncogene JUN Chr: 1p32-p31 2.55 homolog (avian) 201466_s_at v-jun sarcoma virus 17 oncogene JUN Chr: 1p32-p31 2.89 homolog (avian) 213340_s_at KIAA0495 KIAA0495 Chr: 1p36.32 2.95 213271_s_at KIAA1117 protein KIAA1117 Chr: 6q15 0.60 208935_s_at lectin, galactoside-binding, LGALS8 Chr: 1q42-q43 2.56 soluble, 8 (galectin 8) 209205_s_at LIM domain only 4 LMO4 Chr: 1p22.3 2.62 225479_at hypothetical protein LOC116064 LOC116064 Chr: 3q13.33 0.67 227466_at hypothetical protein LOC285550 LOC285550 Chr: 4p15.33 1.54 1558700_s_at hypothetical protein LOC339324 LOC339324 Chr: 19q13.13 2.05 235940_at hypothetical protein MGC10999 MGC10999 Chr: 9q21.33 5.16 228326_at hypothetical protein MGC43690 MGC43690 Chr: 6q27 0.54 213259_s_at similar to RIKEN cDNA MGC9564 Chr: 17q11.2 0.55 1110002C08 gene 224874_at hypothetical protein MGC9850 MGC9850 Chr: 13q12.2 3.26 212080_at myeloid/lymphoid or mixed- MLL Chr: 11q23 0.51 lineage leukemia (trithorax homolog, Drosophila) 208709_s_at nardilysin (N-arginine dibasic NRD1 Chr: 1p32.2-p32.1 1.69 convertase) 209791_at peptidyl arginine deiminase, type PADI2 Chr: 1p35.2-p35.1 4.02 II 207769_s_at polyglutamine binding protein 1 PQBP1 Chr: Xp11.23 0.65 214527_s_at polyglutamine binding protein 1 PQBP1 Chr: Xp11.23 0.65 224909_s_at KIAA1415 protein PRex1 Chr: 20q13.13 2.89 208615_s_at protein tyrosine phosphatase PTP4A2 Chr: 1p35 1.88 type IVA, member 2 208616_s_at protein tyrosine phosphatase PTP4A2 Chr: 1p35 1.87 type IVA, member 2 216988_s_at protein tyrosine phosphatase PTP4A2 Chr: 1p35 1.97 type IVA, member 2 202006_at protein tyrosine phosphatase, PTPN12 Chr: 7q11.23 1.76 non-receptor type 12 201165_s_at pumilio homolog 1 (Drosophila) PUM1 Chr: 1p35.2 1.42 225251_at RAB24, member RAS oncogene RAB24 Chr: 5q35.3 0.53 family 213718_at RNA binding motif protein 4 RBM4 Chr: 11q13 0.47 212197_x_at Rho interacting protein 3 RHOIP3 Chr: 17p11.2 0.66 214143_x_at ribosomal protein L24 RPL24 Chr: 3q12 0.67 211073_x_at ribosomal protein L3 RPL3 Chr: 22q13 0.64 200717_x_at ribosomal protein L7 RPL7 Chr: 8q13.3 0.71 200909_s_at ribosomal protein, large P2 RPLP2 Chr: 11p15.5-p15.4 0.72 208692_at ribosomal protein S3 RPS3 Chr: 11q13.3-q13.5 0.55 202361_at SEC24 related gene family, SEC24C Chr: 10q22.3 0.53 member C (S. cerevisiae) 201696_at splicing factor, arginine/serine- SFRS4 Chr: 1p35.2 1.48 rich 4 220298_s_at spermatogenesis associated 6 SPATA6 Chr: 1p33 5.60 238459_x_at spermatogenesis associated 6 SPATA6 Chr: 1p33 6.03 220299_at spermatogenesis associated 6 SPATA6 Chr: 1p33 4.09 46256_at SPRY domain-containing SOCS SSB3 Chr: 16p13.3 0.66 box protein SSB-3 209022_at stromal antigen 2 STAG2 Chr: Xq25 0.73 201519_at translocase of outer TOMM70A Chr: 3q12.3 0.65 mitochondrial membrane 70 homolog A (yeast) 208661_s_at tetratricopeptide repeat domain 3 TTC3 Chr: 21q22.2 0.46 208662_s_at tetratricopeptide repeat domain 3 TTC3 Chr: 21q22.2 0.51 210645_s_at tetratricopeptide repeat domain 3 TTC3 Chr: 21q22.2 0.50 219043_s_at IAP-associated factor VIAF1 VIAF1 Chr: 2q12.1 0.78 201294_s_at SOCS box-containing WD WSB1 Chr: 17q11.2 0.39 protein SWiP-1 201296_s_at SOCS box-containing WD WSB1 Chr: 17q11.2 0.55 protein SWiP-1 207090_x_at likely ortholog of mouse zinc ZFP30 Chr: 19q13.13 1.63 finger protein 30 228157_at zinc finger protein 207 ZNF207 Chr: 17q12 0.56 222357_at zinc finger protein 288 ZNF288 Chr: 3q13.2 0.30 226252_at hypothetical gene supported by Chr: 3q13.31 0.44 AK022228 227388_at hypothetical gene supported by Chr: 9p21.1 3.48 BC017510; BC036931; BC028316 244740_at LOC342935 Chr: 19q13.43 1.70

TABLE 5 Differentially expressed probesets, which are able to discriminate on basis of loss of heterozygosity (LOH) on the 1p locus ratio loss/no Probe Set ID Title Gene Symbol Location loss 1553954_at hypothetical protein MGC19780 chr1p21.3 0.55 MGC19780 1554433_a_at zinc finger protein 146 ZNF146 chr19q13.1 0.57 1554479_a_at caspase recruitment domain CARD8 chr19q13.32 0.59 family, member 8 1555832_s_at — — — 0.50 1558256_at hypothetical protein LOC148189 chr19q12 0.45 LOC148189 1558604_a_at H. sapiens mRNA; clone CD — — 0.47 43T7 1558700_s_at hypothetical protein LOC339324 chr19q13.12 0.49 LOC339324 200006_at Parkinson disease PARK7 chr1p36.33-p36.12 0.70 (autosomal recessive, early onset) 7 200020_at TAR DNA binding protein TARDBP chr1p36.22 0.70 200050_at zinc finger protein 146 ZNF146 chr19q13.1 0.52 200087_s_at coated vesicle membrane RNP24 chr12q24.31 0.84 protein 200620_at chromosome 1 open reading C1orf8 chr1p36-p31 0.58 frame 8 200625_s_at CAP, adenylate cyclase- CAP1 chr1p34.2 0.61 associated protein 1 (yeast) 200636_s_at protein tyrosine phosphatase, PTPRF chr1p34 0.39 receptor type, F 200650_s_at lactate dehydrogenase A LDHA chr11p15.4 0.26 200686_s_at splicing factor, SFRS11 chr1p31 0.44 arginine/serine-rich 11 200777_s_at basic leucine zipper and W2 BZW1 chr2q33 0.75 domains 1 200791_s_at IQ motif containing GTPase IQGAP1 chr15q26.1 0.27 activating protein 1 200902_at 15 kDa selenoprotei SEP15 chr1p31 0.53 201064_s_at poly(A) binding protein, PABPC4 chr1p32-p36 0.64 cytoplasmic 4 (inducible form) 201080_at phosphatidylinositol-4- PIP5K2B chr17q12 1.63 phosphate 5-kinase, type II, beta 201155_s_at mitofusin 2 MFN2 chr1p36.22 0.64 201164_s_at pumilio homolog 1 PUM1 chr1p35.2 0.52 (Drosophila) 201165_s_at pumilio homolog 1 PUM1 chr1p35.2 0.74 (Drosophila) 201177_s_at SUMO-1 activating enzyme UBA2 chr19q12 0.43 subunit 2 201179_s_at guanine nucleotide binding GNAI3 chr1p13 0.60 protein (G protein), alpha inhibiting activity polypeptide 3 201181_at guanine nucleotide binding GNAI3 chr1p13 0.57 protein (G protein), alpha inhibiting activity polypeptide 3 201209_at histone deacetylase 1 HDAC1 chr1p34 0.44 201225_s_at serine/arginine repetitive SRRM1 chr1p36.11 0.71 matrix 1 201274_at proteasome (prosome, PSMA5 chr1p13 0.60 macropain) subunit, alpha type, 5 201323_at EBNA1 binding protein 2 EBNA1BP2 chr1p35-p33 0.56 201339_s_at sterol carrier protein 2 SCP2 chr1p32 0.56 201398_s_at translocation associated TRAM1 chr8q13.3 0.66 membrane protein 1 201426_s_at vimentin VIM chr10p13 0.39 201445_at calponin 3, acidic CNN3 chr1p22-p21 0.40 201519_at translocase of outer TOMM70A chr3q12.2 1.52 mitochondrial membrane 70 homolog A (yeast) 201667_at gap junction protein, alpha 1, GJA1 chr6q21-q23.2 0.19 43 kDa (connexin 43) 201674_s_at A kinase (PRKA) anchor AKAP1 chr17q21-q23 1.85 protein 1 201696_at splicing factor, SFRS4 chr1p35.3 0.61 arginine/serine-rich 4 201864_at GDP dissociation inhibitor 1 GDI1 chrXq28 1.56 201948_at guanine nucleotide binding GNL2 chr1p34.3 0.49 protein-like 2 (nucleolar) 202049_s_at zinc finger protein 262 ZNF262 chr1p32-p34 0.51 202096_s_at benzodiazapine receptor BZRP chr22q13.31 0.36 (peripheral) 202149_at neural precursor cell NEDD9 chr6p25-p24 0.49 expressed, developmentally down-regulated 9 202250_s_at WD repeat domain 42A WDR42A chr1q22-q23 1.78 202260_s_at syntaxin binding protein 1 STXBP1 chr9q34.1 1.84 202299_s_at hepatitis B virus x interacting HBXIP chr1p13.3 0.57 protein 202300_at hepatitis B virus x interacting HBXIP chr1p13.3 0.59 protein 202361_at SEC24 related gene family, SEC24C chr10q22.2 1.73 member C (S. cerevisiae) 202362_at RAP1A, member of RAS RAP1A chr1p13.3 0.51 oncogene family 202412_s_at ubiquitin specific protease 1 USP1 chr1p32.1-p31.3 0.43 202413_s_at ubiquitin specific protease 1 USP1 chr1p32.1-p31.3 0.41 202471_s_at isocitrate dehydrogenase 3 IDH3G chrXq28 1.54 (NAD+) gamma 202502_at acyl-Coenzyme A ACADM chr1p31 0.57 dehydrogenase, C-4 to C-12 straight chain 202625_at v-yes-1 Yamaguchi sarcoma LYN chr8q13 0.46 viral related oncogene homolog 202626_s_at v-yes-1 Yamaguchi sarcoma LYN chr8q13 0.43 viral related oncogene homolog 202668_at ephrin-B2 EFNB2 chr13q33 0.42 202669_s_at ephrin-B2 EFNB2 chr13q33 0.50 202868_s_at POP4 (processing of POP4 chr19q12 0.63 precursor, S. cerevisiae) homolog 202939_at zinc metalloproteinase ZMPSTE24 chr1p34 0.53 (STE24 homolog, yeast) 202950_at crystallin, zeta (quinone CRYZ chr1p31-p22 0.43 reductase) 203069_at synaptic vesicle glycoprotein SV2A chr1q21.2 1.96 2A 203221_at transducin-like enhancer of TLE1 chr9q21.32 0.31 split 1 (E(sp1) homolog, Drosophila) 203222_s_at transducin-like enhancer of TLE1 chr9q21.32 0.33 split 1 (E(sp1) homolog, Drosophila) 203283_s_at heparan sulfate 2-O- HS2ST1 chr1p31.1-p22.1 0.29 sulfotransferase 1 203284_s_at heparan sulfate 2-O- HS2ST1 chr1p31.1-p22.1 0.51 sulfotransferase 1 203288_at KIAA0355 KIAA0355 chr19q13.11 0.60 203289_s_at chromosome 16 open reading C16orf35 chr16p13.3 2.09 frame 35 203303_at t-complex-associated-testis- TCTE1L chrXp21 0.33 expressed 1-like 203310_at syntaxin binding protein 3 STXBP3 chr1p13.3 0.48 203347_s_at likely ortholog of mouse metal M96 chr1p22.1 0.44 response element binding transcription factor 2 203364_s_at KIAA0652 gene product KIAA0652 chr11p11.2 1.59 203389_at kinesin family member 3C KIF3C chr2p23 2.12 203401_at phosphoribosyl PRPS2 chrXp22.3-p22.2 0.35 pyrophosphate synthetase 2 203511_s_at trafficking protein particle TRAPPC3 chr1p34.3 0.55 complex 3 203560_at gamma-glutamyl hydrolase GGH chr8q12.3 0.37 (conjugase, folylpolygammaglutamyl hydrolase) 203611_at telomeric repeat binding TERF2 chr16q22.1 1.59 factor 2 203765_at grancalcin, EF-hand calcium GCA chr2q24.2 0.32 binding protein 203787_at single-stranded DNA binding SSBP2 chr5q14.1 0.38 protein 2 203819_s_at IGF-II mRNA-binding protein 3 IMP-3 chr7p11 0.05 203928_x_at microtubule-associated MAPT chr17q21.1 2.57 protein tau 203930_s_at microtubule-associated MAPT chr17q21.1 2.44 protein tau 204011_at sprouty homolog 2 SPRY2 chr13q31.1 0.33 (Drosophila) 204022_at Nedd-4-like ubiquitin-protein WWP2 chr16q22.1 1.93 ligase 204036_at endothelial differentiation, EDG2 chr9q31.3 0.15 lysophosphatidic acid G- protein-coupled receptor, 2 204228_at peptidyl prolyl isomerase H PPIH chr1p34.1 0.49 (cyclophilin H) 204299_at FUS interacting protein FUSIP1 chr1p36.11 0.52 (serine-arginine rich) 1 204363_at coagulation factor III F3 chr1p22-p21 0.16 (thromboplastin, tissue factor) 204379_s_at fibroblast growth factor FGFR3 chr4p16.3 0.20 receptor 3 (achondroplasia, thanatophoric dwarfism) 204400_at embryonal Fyn-associated EFS chr14q11.2-q12 2.55 substrate 204451_at frizzled homolog 1 FZD1 chr7q21 0.38 (Drosophila) 204722_at sodium channel, voltage- SCN3B chr11q24.1 4.57 gated, type II, beta 204984_at glypican 4 GPC4 chrXq26.1 0.40 205095_s_at ATPase, H+ transporting, ATP6V0A1 chr17q21 1.80 lysosomal V0 subunit a isoform 1 205130_at renal tumor antigen RAGE chr14q32 0.52 205140_at fucose-1-phosphate FPGT chr1p31.1 0.36 guanylytransferase 205173_x_at CD58 antigen, (lymphocyte CD58 chr1p13 0.22 function-associated antigen 3) 205176_s_at integrin beta 3 binding protein ITGB3BP chr1p31.3 0.48 (beta3-endonexin) 205260_s_at acylphosphatase 1, ACYP1 chr14q24.3 0.44 erythrocyte (common) type 205263_at B-cell CLL/lymphoma 10 BCL10 chr1p22 0.54 205292_s_at heterogeneous nuclear HNRPA2B1 chr7p15 0.72 ribonucleoprotein A2/B1 205497_at zinc finger protein 175 ZNF175 chr19q13.4 0.63 205852_at cyclin-dependent kinase 5, CDK5R2 chr2q35 2.45 regulatory subunit 2 (p39) 205996_s_at adenylate kinase 2 AK2 chr1p34 0.59 206095_s_at FUS interacting protein FUSIP1 chr1p36.11 0.43 (serine-arginine rich) 1 206401_s_at microtubule-associated MAPT chr17q21.1 2.72 protein tau 206993_at ATP synthase, H+ ATP5S chr14q21.3 1.42 transporting, mitochondrial F0 complex, subunit s (factor B) 207090_x_at zinc finger protein KIAA0961 KIAA0961 chr19q13.13 0.61 207236_at zinc finger protein 345 ZNF345 chr19q13.12 0.45 207358_x_at microtubule-actin crosslinking MACF1 chr1p32-p31 0.54 factor 1 208095_s_at signal recognition particle SRP72 chr4q11 0.66 72 kDa 208374_s_at capping protein (actin CAPZA1 chr1p13.2 0.55 filament) muscle Z-line, alpha 1 208615_s_at protein tyrosine phosphatase PTP4A2 chr1p35 0.51 type IVA, member 2 208680_at peroxiredoxin 1 PRDX1 chr1p34.1 0.33 208709_s_at nardilysin (N-arginine dibasic NRD1 chr1p32.2-p32.1 0.60 convertase) 208723_at ubiquitin specific protease 11 USP11 chrXp11.23 1.92 208728_s_at cell division cycle 42 (GTP CDC42 chr1p36.1 0.55 binding protein, 25 kDa) 208766_s_at heterogeneous nuclear HNRPR chr1p36.12 0.67 ribonucleoprotein R 208924_at ring finger protein 11 RNF11 chr1pter-p22.1 0.65 208971_at uroporphyrinogen UROD chr1p34 0.63 decarboxylase 209001_s_at anaphase promoting complex ANAPC13 chr3q22.1 1.32 subunit 13 209045_at X-prolyl aminopeptidase XPNPEP1 chr10q25.3 1.44 (aminopeptidase P) 1, soluble 209099_x_at jagged 1 (Alagille syndrome) JAG1 chr20p12.1-p11.23 0.38 209117_at WW domain binding protein 2 WBP2 chr17q25 2.05 209120_at nuclear receptor subfamily 2, NR2F2 chr15q26 0.33 group F, member 2 209187_at down-regulator of DR1 chr1p22.1 0.46 transcription 1, TBP-binding (negative cofactor 2) 209355_s_at phosphatidic acid PPAP2B chr1pter-p22.1 0.25 phosphatase type 2B 209537_at exostoses (multiple)-like 2 EXTL2 chr1p21 0.61 209669_s_at PAI-1 mRNA-binding protein PAI-RBP1 chr1p31-p22 0.48 209707_at phosphatidylinositol glycan, PIGK chr1p31.1 0.62 class K 209711_at solute carrier family 35 (UDP- SLC35D1 chr1p32-p31 0.49 glucuronic acid/UDP-N- acetylgalactosamine dual transporter), member D1 209875_s_at secreted phosphoprotein 1 SPP1 chr4q21-q25 0.22 (osteopontin, bone sialoprotein I, early T- lymphocyte activation 1) 210092_at mago-nashi homolog, MAGOH chr1p34-p33 0.40 proliferation-associated (Drosophila) 210093_s_at mago-nashi homolog, MAGOH chr1p34-p33 0.51 proliferation-associated (Drosophila) 210137_s_at dCMP deaminase DCTD chr4q35.1 0.17 210178_x_at FUS interacting protein FUSIP1 chr1p36.11 0.54 (serine-arginine rich) 1 210191_s_at putative homeodomain PHTF1 chr1p13 0.65 transcription factor 1 210371_s_at retinoblastoma binding RBBP4 chr1p35.1 0.48 protein 4 210502_s_at peptidylprolyl isomerase E PPIE chr1p32 0.54 (cyclophilin E) 210517_s_at A kinase (PRKA) anchor AKAP12 chr6q24-q25 0.36 protein (gravin) 12 210645_s_at tetratricopeptide repeat TTC3 chr21q22.2 1.94 domain 3 210754_s_at v-yes-1 Yamaguchi sarcoma LYN chr8q13 0.57 viral related oncogene homolog 210770_s_at calcium channel, voltage- CACNA1A chr19p13.2-p13.1 3.12 dependent, P/Q type, alpha 1A subunit 210829_s_at single-stranded DNA binding SSBP2 chr5q14.1 0.33 protein 2 210840_s_at IQ motif containing GTPase IQGAP1 chr15q26.1 0.32 activating protein 1 211383_s_at WD repeat domain 37 WDR37 chr10p15.3 1.34 211474_s_at serine (or cysteine) SERPINB6 chr6p25 0.54 proteinase inhibitor, clade B (ovalbumin), member 6 211488_s_at integrin, beta 8 ITGB8 chr7p21.1 0.55 211662_s_at voltage-dependent anion VDAC2 chr10q22 1.62 channel 2 211703_s_at beta-amyloid binding protein BBP chr1p31.3 0.44 precursor 211733_x_at sterol carrier protein 2 SCP2 chr1p32 0.64 211755_s_at ATP synthase, H+ ATP5F1 chr1p13.2 0.67 transporting, mitochondrial F0 complex, subunit b, isoform 1 212131_at family with sequence FAM61A chr19q13.11 0.48 similarity 61, member A 212132_at family with sequence FAM61A chr19q13.11 0.35 similarity 61, member A 212192_at potassium channel KCTD12 chr13q22.3 0.36 tetramerisation domain containing 12 212226_s_at phosphatidic acid PPAP2B chr1pter-p22.1 0.33 phosphatase type 2B 212230_at phosphatidic acid PPAP2B chr1pter-p22.1 0.32 phosphatase type 2B 212245_at multiple coagulation factor MCFD2 chr2p21 0.66 deficiency 2 212294_at guanine nucleotide binding GNG12 chr1p31.2 0.24 protein (G protein), gamma 12 212355_at KIAA0323 protein KIAA0323 chr14q11.2 0.49 212370_x_at family with sequence FAM21B chr10q11.22 /// 1.61 similarity 21, member B chr10q11.23 212383_at ATPase, H+ transporting, ATP6V0A1 chr17q21 1.74 lysosomal V0 subunit a isoform 1 212393_at SET binding factor 1 SBF1 chr22q13.33 1.77 212491_s_at DnaJ (Hsp40) homolog, DNAJC8 chr1p35.3 0.56 subfamily C, member 8 212503_s_at KIAA0934 protein KIAA0934 chr10p15.3 1.29 212513_s_at ubiquitin specific protease 33 USP33 chr1p31.1 0.53 212515_s_at DEAD (Asp-Glu-Ala-Asp) box DDX3X chrXp11.3-p11.23 0.74 polypeptide 3, X-linked 212628_at Protein kinase N2 PKN2 chr1p22.2 0.47 212698_s_at septin 10 SEPT10 chr2q13 0.43 212699_at secretory carrier membrane SCAMP5 chr15q23 2.34 protein 5 212893_at zinc finger, ZZ domain ZZZ3 chr1p31.1 0.49 containing 3 212920_at Homo sapiens transcribed — — 0.40 sequence with weak similarity to protein ref: NP_060312.1 (H. sapiens) hypothetical protein FLJ20489 [Homo sapiens] 212928_at TSPY-like 4 TSPYL4 chr6q22.1 1.41 213001_at angiopoietin-like 2 ANGPTL2 chr9q34 3.95 213004_at angiopoietin-like 2 ANGPTL2 chr9q34 4.16 213156_at Homo sapiens mRNA; cDNA — — 1.89 DKFZp586B211 (from clone DKFZp586B211) 213158_at Homo sapiens mRNA; cDNA — — 1.66 DKFZp586B211 (from clone DKFZp586B211) 213170_at glutathione peroxidase 7 GPX7 chr1p32 0.52 213186_at zinc finger DAZ interacting DZIP3 chr3q13.13 1.48 protein 3 213259_s_at sterile alpha and TIR motif SARM1 chr17q11 1.87 containing 1 213340_s_at KIAA0495 KIAA0495 chr1p36.32 0.35 213351_s_at transmembrane and coiled- TMCC1 chr3q21.3 1.62 coil domains 1 213424_at KIAA0895 protein KIAA0895 chr7p14.1 0.66 213436_at cannabinoid receptor 1 CNR1 chr6q14-q15 0.32 (brain) 213439_x_at RaP2 interacting protein 8 RPIP8 chr17q21.31 2.77 213464_at SHC (Src homology 2 domain SHC2 chr19p13.3 2.03 containing) transforming protein 2 213467_at FALSE — — 2.59 213557_at CDC2-related protein kinase 7 CRK7 chr17q12 1.67 213798_s_at CAP, adenylate cyclase- CAP1 chr1p34.2 0.57 associated protein 1 (yeast) 213883_s_at beta-amyloid binding protein BBP chr1p31.3 0.52 precursor 214241_at NADH dehydrogenase NDUFB8 chr10q23.2-q23.33 1.66 (ubiquinone) 1 beta subcomplex, 8, 19 kDa 214383_x_at kelch domain containing 3 KLHDC3 chr6p21.1 1.44 214894_x_at microtubule-actin crosslinking MACF1 chr1p32-p31 0.58 factor 1 214933_at calcium channel, voltage- CACNA1A chr19p13.2-p13.1 2.72 dependent, P/Q type, alpha 1A subunit 215017_s_at formin binding protein 1-like FNBP1L chr1p22.1 0.20 215222_x_at microtubule-actin crosslinking MACF1 chr1p32-p31 0.50 factor 1 215691_x_at chromosome 1 open reading C1orf41 chr1p32.1-p33 0.44 frame 41 216268_s_at jagged 1 (Alagille syndrome) JAG1 chr20p12.1-p11.23 0.39 216903_s_at calcium binding atopy-related CBARA1 chr10q22.1 1.67 autoantigen 1 217724_at PAI-1 mRNA-binding protein PAI-RBP1 chr1p31-p22 0.67 217877_s_at hypothetical protein SP192 SP192 chr1p34.1 0.44 217893_s_at hypothetical protein FLJ12666 chr1p34.3 0.50 FLJ12666 217921_at — — 0.56 217968_at tumor suppressing TSSC1 chr2p25.2 1.52 subtransferable candidate 1 218011_at ubiquitin-like 5 UBL5 chr19p13.3 0.57 218097_s_at CUE domain containing 2 CUEDC2 chr10q24.32 1.46 218302_at presenilin enhancer 2 PSENEN chr19q13.12 0.50 homolog (C. elegans) 218370_s_at hypothetical protein FLJ12903 chr1p35.1 0.61 FLJ12903 218462_at RNA processing factor 1 RPF1 chr1p22.3 0.44 218490_s_at zinc finger protein 302 ZNF302 chr19q13.11 0.49 218577_at hypothetical protein FLJ20331 chr1p31.1 0.62 FLJ20331 218640_s_at pleckstrin homology domain PLEKHF2 chr8q22.1 0.32 containing, family F (with FYVE domain) member 2 218712_at hypothetical protein FLJ20508 chr1p34.3 0.48 FLJ20508 218924_s_at chitobiase, di-N-acetyl- CTBS chr1p22 0.37 218938_at F-box and leucine-rich repeat FBXL15 chr10q24.32 2.59 protein 15 219094_at armadillo repeat containing 8 ARMC8 chr3q22.3 1.53 219314_s_at zinc finger protein 219 ZNF219 chr14q11 1.88 219372_at carnitine deficiency- CDV1 chr12q24.13 0.60 associated, expressed in ventricle 1 219375_at choline/ethanolaminephospho CEPT1 chr1p13.3 0.58 transferase 219494_at RAD54B homolog RAD54B chr8q21.3-q22 0.34 219818_s_at G patch domain containing 1 GPATC1 chr19q13.11 0.52 219848_s_at zinc finger protein 432 ZNF432 chr19q13.41 0.53 219939_s_at upstream of NRAS UNR chr1p22 0.65 220358_at Jun dimerization protein SNFT chr1q32.3 0.47 p21SNFT 220443_s_at ventral anterior homeobox 2 VAX2 chr2p13 2.58 221024_s_at solute carrier family 2 SLC2A10 chr20q13.1 0.09 (facilitated glucose transporter), member 10 221432_s_at solute carrier family 25, SLC25A28 chr10q23-q24 1.72 member 28 221486_at endosulfine alpha ENSA chr1q21.2 1.66 221522_at ankyrin repeat domain 27 ANKRD27 chr19q13.11 0.62 (VPS9 domain) 221679_s_at abhydrolase domain ABHD6 chr3p14.3 1.90 containing 6 221958_s_at putative NFkB activating FLJ23091 chr1p31.2 0.35 protein 373 222409_at coronin, actin binding protein, CORO1C chr12q24.1 1.60 1C 222452_s_at hypothetical protein SP192 SP192 chr1p34.1 0.50 222459_at hypothetical protein FLJ12666 chr1p34.3 0.59 FLJ12666 222495_at protein x 013 AD-020 chr1p13.3 0.54 222580_at zinc finger protein 644 ZNF644 chr1p22.2 0.57 222654_at myo-inositol IMPA3 chr8q12.1 0.60 monophosphatase A3 222699_s_at pleckstrin homology domain PLEKHF2 chr8q22.1 0.34 containing, family F (with FYVE domain) member 2 222833_at hypothetical protein FLJ20481 chr16q12.2 0.25 FLJ20481 222834_s_at guanine nucleotide binding GNG12 chr1p31.2 0.40 protein (G protein), gamma 12 222893_s_at hypothetical protein FLJ13150 chr1p22.1 0.55 FLJ13150 222975_s_at upstream of NRAS UNR chr1p22 0.62 223017_at endoplasmic reticulum TLP19 chr1p32.3 0.48 thioredoxin superfamily member, 18 kDa 223042_s_at FUN14 domain containing 2 FUNDC2 chrXq28 1.47 223066_at SNARE associated protein SNAPAP chr1q21.3 0.65 snapin 223103_at START domain containing 10 STARD10 chr11q13 2.40 223120_at fucosidase, alpha-L-2, FUCA2 chr6q24 0.34 plasma 223125_s_at chromosome 1 open reading C1orf21 chr1q25 0.51 frame 21 223132_s_at tripartite motif-containing 8 TRIM8 chr10q24.3 1.84 223159_s_at NIMA (never in mitosis gene NEK6 chr9q33.3-q34.11 0.36 a)-related kinase 6 223230_at hypothetical protein FLJ14936 chr1p33-p32.1 0.58 FLJ14936 223296_at mitochondrial carrier protein MGC4399 chr1p36.22 0.65 223331_s_at DEAD (Asp-Glu-Ala-Asp) box DDX20 chr1p21.1-p13.2 0.53 polypeptide 20 223398_at chromosome 9 open reading C9orf89 chr9q22.31 0.22 frame 89 223418_x_at hypothetical protein DKFZP566D1346 chr1p32.3-p31.3 0.58 DKFZp566D1346 223435_s_at protocadherin alpha PCDHA9 /// chr5q31 2.25 9///protocadherin alpha PCDHAC2 /// subfamily C, 2///protocadherin PCDHAC1 /// alpha subfamily C, PCDHA13 /// 1///protocadherin alpha PCDHA12 /// 13///protocadherin alpha PCDHA11 /// 12///protocadherin alpha PCDHA10 /// 11///protocadherin alpha PCDHA8 /// 10///protocadherin alpha PCDHA7 /// 8///protocadherin alpha PCDHA6 /// 7///protocadherin alpha PCDHA5 /// 6///protocadherin alpha PCDHA4 /// 5///protocadherin alpha PCDHA3 /// 4///protocadherin alpha PCDHA2 /// 3///protocadherin alpha PCDHA1 2///protocadherin alpha 1 223500_at complexin 1 CPLX1 chr4p16.3 3.79 223603_at zinc finger protein 179 ZNF179 chr17p11.2 2.71 223824_at chromosome 10 open reading C10orf59 chr10q23.31 0.60 frame 59 224212_s_at protocadherin alpha PCDHA9 /// chr5q31 2.12 9///protocadherin alpha PCDHAC2 /// subfamily C, 2///protocadherin PCDHAC1 /// alpha subfamily C, PCDHA13 /// 1///protocadherin alpha PCDHA12 /// 13///protocadherin alpha PCDHA11 /// 12///protocadherin alpha PCDHA10 /// 11///protocadherin alpha PCDHA8 /// 10///protocadherin alpha PCDHA7 /// 8///protocadherin alpha PCDHA6 /// 7///protocadherin alpha PCDHA5 /// 6///protocadherin alpha PCDHA4 /// 5///protocadherin alpha PCDHA3 /// 4///protocadherin alpha PCDHA2 /// 3///protocadherin alpha PCDHA1 2///protocadherin alpha 1 224280_s_at hypothetical protein RP1- LOC56181 chr1p36.11 0.49 317E23 224315_at DEAD (Asp-Glu-Ala-Asp) box DDX20 chr1p21.1-p13.2 0.58 polypeptide 20 224565_at trophoblast-derived TncRNA chr11q13.1 0.32 noncoding RNA 224591_at HP1-BP74 HP1-BP74 chr1p36.12 0.60 224686_x_at Homo sapiens transcribed — chr17q21.32 1.47 sequence with strong similarity to protein ref: NP_060471.1 (H. sapiens) hypothetical protein FLJ10120 [Homo sapiens] 224867_at similar to protein of fungal LOC440574 chr1p36.13 0.51 metazoan origin like (11.1 kD) (2C514) 224909_s_at KIAA1415 protein PREX1 chr20q13.13 0.37 224925_at KIAA1415 protein PREX1 chr20q13.13 0.34 224937_at prostaglandin F2 receptor PTGFRN chr1p13.1 0.44 negative regulator 224985_at neuroblastoma RAS viral (v- NRAS chr1p13.2 0.63 ras) oncogene homolog 225222_at hippocampus abundant gene HIAT1 chr1p21.3 0.58 transcript 1 225327_at hypothetical protein FLJ10980 chr15q21.2-q21.3 1.81 FLJ10980 225379_at microtubule-associated MAPT chr17q21.1 1.89 protein tau 225382_at zinc finger protein 275 ZNF275 chrXq28 2.37 225384_at dedicator of cytokinesis 7 DOCK7 chr1p31.3 0.40 225475_at mesoderm induction early MI-ER1 chr1p31.2 0.51 response 1 225479_at CDNA FLJ32247 fis, clone — — 1.46 PROST1000120 225612_s_at UDP-GlcNAc:betaGal beta- B3GNT5 chr3q28 0.30 1,3-N- acetylglucosaminyltransferase 5 225633_at hypothetical protein LOC147991 chr19q13.11 0.64 LOC147991 225878_at kinesin family member 1B KIF1B chr1p36.2 0.59 225925_s_at ubiquitin specific protease 48 USP48 chr1p36.12 0.58 226000_at hypothetical protein DKFZp547A023 chr1p13.2 0.43 DKFZp547A023 226116_at Homo sapiens cDNA — — 0.72 FLJ12540 fis, clone NT2RM4000425. 226189_at Homo sapiens, clone — — 0.46 IMAGE: 4794726, mRNA 226294_x_at hypothetical protein FLJ23790 chr8q24.13 0.70 FLJ23790 226411_at ecotropic viral integration site EVI5L chr19p13.2 2.15 5-like 226458_at Homo sapiens, clone — — 0.53 IMAGE: 4449283, mRNA 226487_at hypothetical protein FLJ14721 chr12q24.11 3.21 FLJ14721 226517_at branched chain BCAT1 chr12pter-q12 0.17 aminotransferase 1, cytosolic 226532_at Homo sapiens transcribed — — 0.49 sequence with weak similarity to protein ref: NP_055301.1 (H. sapiens) neuronal thread protein [Homo sapiens] 226601_at solute carrier family 30 (zinc SLC30A7 chr1p21.2 0.65 transporter), member 7 226630_at chromosome 14 open reading C14orf106 chr14q21.3 0.49 frame 106 226760_at hypothetical protein LOC203411 chrXp22.13 1.38 LOC203411 226909_at KIAA1729 protein KIAA1729 chr4p16.1 0.20 226976_at Karyopherin alpha 6 (importin KPNA6 chr1p35.1-p34.3 0.55 alpha 7) 227081_at dynein, axonemal, light DNALI1 chr1p35.1 0.34 intermediate polypeptide 1 227091_at KIAA1505 protein KIAA1505 chr7p12.3 0.59 227112_at — — — 1.96 227154_at hypothetical protein MGC15730 chr1p36.13 2.74 MGC15730 227199_at Chromosome 21 open C21orf106 chr21q22.3 1.53 reading frame 106 227222_at F-box only protein 10 FBXO10 chr9p13.2 1.73 227270_at hypothetical protein LOC285550 chr4p15.33 0.47 LOC285550 227278_at Homo sapiens transcribed — — 0.48 sequence with weak similarity to protein ref: NP_055301.1 (H. sapiens) neuronal thread protein [Homo sapiens] 227334_at ubiquitin specific protease 54 USP54 chr10q22.2 2.18 227361_at heparan sulfate HS3ST3B1 chr17p12-p11.2 0.08 (glucosamine) 3-O- sulfotransferase 3B1 227388_at tumor suppressor candidate 1 TUSC1 chr9p21.1 0.39 227449_at EPH receptor A4 EPHA4 chr2q36.1 0.32 227456_s_at chromosome 6 open reading C6orf136 chr6p21.33 1.59 frame 136 227573_s_at KIAA0657 protein KIAA0657 chr2q35 1.71 227639_at phosphatidylinositol glycan, PIGK chr1p31.1 0.51 class K 227674_at zinc finger protein 585A ZNF585A chr19q13.12 0.32 227680_at zinc finger protein 326 ZNF326 chr1p22.2 0.56 227812_at tumor necrosis factor receptor TNFRSF19 chr13q12.11-q12.3 0.25 superfamily, member 19 227845_s_at src homology 2 domain- SHD chr19p13.3 5.98 containing transforming protein D 227889_at hypothetical protein FLJ20481 chr16q12.2 0.40 FLJ20481 227898_s_at hypothetical protein FLJ38705 chr8q24.3 1.73 FLJ38705 228020_at hypothetical protein FLJ20758 chr2p11.2 1.64 FLJ20758 228135_at chromosome 1 open reading C1orf52 chr1p22.3 0.52 frame 52 228165_at hypothetical protein DKFZp547D2210 chr12p13.31 2.36 DKFZp547D2210 228190_at — — — 0.43 228284_at transducin-like enhancer of TLE1 chr9q21.32 0.45 split 1 (E(sp1) homolog, Drosophila) 228415_at adaptor-related protein AP1S2 chrXp22.2 0.35 complex 1, sigma 2 subunit 228422_at Homo sapiens, clone — — 2.08 IMAGE: 5300488, mRNA 228538_at zinc finger protein 662 ZNF662 chr3p22.1 0.33 228600_x_at hypothetical protein MGC72075 chr7p15.3 0.12 MGC72075 228652_at hypothetical protein FLJ38288 chr19q13.43 0.55 FLJ38288 228730_s_at secernin 2 SCRN2 chr17q21.32 1.63 228805_at FLJ44216 protein FLJ44216 chr5q35.2 0.41 228813_at histone deacetylase 4 HDAC4 chr2q37.2 2.68 228949_at putative NFkB activating FLJ23091 chr1p31.2 0.30 protein 373 228950_s_at putative NFkB activating FLJ23091 chr1p31.2 0.40 protein 373 228970_at archease ARCH chr1p35.1 0.54 229228_at cAMP responsive element CREB5 chr7p15.1 0.34 binding protein 5 229299_at hypothetical protein FLJ30596 chr5p13.2 0.35 FLJ30596 229318_at Homo sapiens transcribed — — 1.71 sequences 229435_at GLIS family zinc finger GLIS3 chr9p24.2 0.20 229498_at Homo sapiens transcribed — — 0.29 sequences 230258_at GLIS family zinc finger GLIS3 chr9p24.2 0.34 230350_at Homo sapiens transcribed — — 1.87 sequence with moderate similarity to protein ref: NP_060312.1 (H. sapiens) hypothetical protein FLJ20489 [Homo sapiens] 230352_at Phosphoribosyl PRPS2 chrXp22.3-p22.2 0.25 pyrophosphate synthetase 2 230637_at sideroflexin 4 SFXN4 chr10q26.11 2.62 231118_at ankyrin repeat domain 35 ANKRD35 chr1q21.1 0.33 231183_s_at Jagged 1 (Alagille syndrome) JAG1 chr20p12.1-p11.23 0.44 231774_at calsenilin, presenilin binding CSEN chr2q21.1 2.40 protein, EF hand transcription factor 231924_at Homo sapiens cDNA — chr11p15.2 0.45 FLJ10570 fis, clone NT2RP2003117. 231940_at zinc finger protein 529 ZNF529 chr19q13.13 0.64 232195_at G protein-coupled receptor GPR158 chr10p12.1 3.45 158 232322_x_at START domain containing 10 STARD10 chr11q13 1.93 234140_s_at stromal interaction molecule 2 STIM2 chr4p15.2 0.48 234672_s_at hypothetical protein FLJ10407 chr1p32.3 0.49 FLJ10407 235015_at zinc finger, DHHC domain ZDHHC9 chrXq26.1 1.79 containing 9 235058_at Hypothetical protein FLJ10349 chr1p36.11 0.64 FLJ10349 235414_at zinc finger protein 383 ZNF383 chr19q13.12 0.48 235431_s_at pellino 3 alpha MGC35521 chr11q13.2 2.20 235500_at heterogeneous nuclear HNRPC chr14q11.2 1.82 ribonucleoprotein C (C1/C2) 235509_at hypothetical protein MGC40214 chr8q22.1 0.37 MGC40214 235648_at zinc finger protein 567 ZNF567 chr19q13.12 0.47 235721_at deltex 3 homolog DTX3 chr12q13.3 1.67 (Drosophila) 235759_at EF hand calcium binding EFCBP1 chr8q21.3 0.19 protein 1 235916_at yippee-like 4 (Drosophila) YPEL4 chr11q12.1 2.86 235940_at chromosome 9 open reading C9orf64 chr9q21.32 0.25 frame 64 235969_at hypothetical protein FLJ33996 chr12q13.13 1.67 FLJ33996 238547_at hypothetical protein HEXIM2 chr17q21.31 1.58 MGC39389 239108_at Male sterility domain MLSTD1 chr12p11.22 0.41 containing 1 239442_at KIAA0582 protein KIAA0582 chr2p14 1.93 240841_at insulinoma-associated 2 INSM2 chr14q13.2 2.38 241858_at fucose-1-phosphate FPGT chr1p31.1 0.40 guanylyltransferase 242263_at CGI-100 protein CGI-100 chr1pter-q31.3 0.57 242269_at FLJ42875 protein FLJ42875 chr1p36.32 0.40 242429_at zinc finger protein 567 ZNF567 chr19q13.12 0.51 243042_at FLJ35093 protein FLJ35093 chr1p31.1 0.55 244462_at inc finger protein 224 ZNF224 chr19q13.2 0.53 244740_at hypothetical protein MGC9913 chr19q13.43 0.64 MGC9913 33760_at peroxisomal biogenesis factor PEX14 chr1p36.22 0.60 14 38398_at MAP-kinase activating death MADD chr11p11.2 1.50 domain 38710_at OTU domain, ubiquitin OTUB1 chr11q13.1 1.44 aldehyde binding 1

TABLE 6 Differentially expressed probesets, which are able to discriminate on basis of loss of heterozygosity (LOH) on the 19q locus ratio loss/no Probe Set ID Title Gene Symbol location loss 200650_s_at lactate dehydrogenase A LDHA Chr: 11p15.4 0.31 21058_s_at chemokine-like factor CKLF Chr: 16q22.1 0.67 218624_s_at hypothetical protein MGC2752 Chr: 19p13.2 0.56 MGC2752 200826_at small nuclear SNRPD2 Chr: 19q13.2 0.49 ribonucleoprotein D2 polypeptide 16.5 kDa 219603_s_at zinc finger protein 226 ZNF226 Chr: 19q13.2 0.35 222028_at zinc finger protein 45 (a ZNF45 Chr: 19q13.2 0.55 Kruppel-associated box (KRAB) domain polypeptide) 229123_at zinc finger protein 224 ZNF224 Chr: 19q13.2 0.54 244462_at zinc finger protein 224 ZNF224 Chr: 19q13.2 0.52 219495_s_at zinc finger protein 180 ZNF180 Chr: 19q13.2 0.57 (HHZ168) 206175_x_at zinc finger protein 222 ZNF222 Chr: 19q13.2 0.43 228131_at excision repair cross- ERCC1 Chr: 19q13.2-q13.3 0.51 complementing rodent repair deficiency, complementation group 1 (includes overlapping antisense sequence) 201194_at selenoprotein W, 1 SEPW1 Chr: 19q13.3 0.48 225434_at death effector domain- DEDD2 Chr: 19q13.31 0.49 containing DNA binding protein 2 227689_at zinc finger protein 227 ZNF227 Chr: 19q13.32 0.57 202153_s_at nucleoporin 62 kDa NUP62 Chr: 19q13.33 0.47 209751_s_at spondyloepiphyseal SEDL/SEDLP Chr: 19q13.4 0.54 dysplasia, late 207753_at zinc finger protein 304 ZNF304 Chr: 19q13.4 0.53 205497_at zinc finger protein 175 ZNF175 Chr: 19q13.4 0.62 1556678_a_at Homo sapiens full — Chr: 19q13.41 0.59 length insert cDNA clone ZD41C11 219848_s_at zinc finger protein 432 ZNF432 Chr: 19q13.41 0.51 202408_s_at PRP31 pre-mRNA PRPF31 Chr: 19q13.42 0.49 processing factor 31 homolog (yeast) 229614_at hypothetical protein LOC162967 Chr: 19q13.42 0.62 LOC162967 225256_at Homo sapiens Chr: 19q13.43 0.55 transcribed sequence with weak similarity to protein ref: NP_071431.1 (H. sapiens) cytokine receptor-like factor 2; cytokine receptor CRL2 precusor [Homo sapiens] 238436_s_at Homo sapiens — Chr: 19q13.43 0.64 transcribed sequences 238437_at Homo sapiens — Chr: 19q13.43 0.60 transcribed sequences 228652_at hypothetical protein FLJ38288 Chr: 19q13.43 0.51 FLJ38288 244741_s_at LOC342935 Chr: 19q13.43 0.61 244740_at LOC342935 Chr: 19q13.43 0.65 201274_at proteasome (prosome, PSMA5 Chr: 1p13 0.60 macropain) subunit, alpha type, 5 211755_s_at ATP synthase, H+ ATP5F1 Chr: 1p13.2 0.68 transporting, mitochondrial F0 complex, subunit b, isoform 1 224729_s_at ATP synthase ATPAF1 Chr: 1p33 0.48 mitochondrial F1 complex assembly factor 1 218080_x_at Fas (TNFRSF6) FAF1 Chr: 1p33 0.51 associated factor 1 213622_at collagen, type IX, alpha 2 COL9A2 Chr: 1p33-p32 0.38 203359_s_at c-myc binding protein MYCBP Chr: 1p33-p32.2 0.51 228970_at archease ARCH Chr: 1p34.3 0.53 202139_at aldo-keto reductase AKR7A2 Chr: 1p35.1-p36.23 0.58 family 7, member A2 (aflatoxin aldehyde reductase) 212491_s_at DnaJ (Hsp40) homolog, DNAJC8 Chr: 1p35.3 0.61 subfamily C, member 8 201225_s_at serine/arginine SRRM1 Chr: 1p36.11 0.71 repetitive matrix 1 224867_at similar to Putative Chr: 1p36.13 0.54 protein of fungal and metazoan origin (11.1 kD) 212401_s_at cell division cycle 2-like 2 CDC2L2 Chr: 1p36.3 0.70 222000_at hypothetical protein LOC339448 Chr: 1p36.32 0.66 LOC339448 213340_s_at KIAA0495 KIAA0495 Chr: 1p36.32 0.38 220526_s_at mitochondrial ribosomal MRPL20 Chr: 1p36.3-p36.2 0.56 protein L20 202297_s_at RER1 homolog (S. cerevisiae) RER1 Chr: 1p36.32 0.50 236369_at Homo sapiens — Chr: 20q11.21 1.38 transcribed sequence with weak similarity to protein prf: 2109260A (H. sapiens) 2109260A B cell growth factor [Homo sapiens] 202096_s_at benzodiazapine BZRP Chr: 22q13.31 0.39 receptor (peripheral) 228538_at similar to Zinc finger Chr: 3p21.33 0.43 protein 7 (Zinc finger protein KOX4) (Zinc finger protein HF.16) 202763_at caspase 3, apoptosis- CASP3 Chr: 4q34 0.51 related cysteine protease 201572_x_at dCMP deaminase DCTD Chr: 4q35.1 0.28 210137_s_at dCMP deaminase DCTD Chr: 4q35.1 0.18 201571_s_at dCMP deaminase DCTD Chr: 4q35.1 0.28 233103_at Homo sapiens cDNA — Chr: 5q14.1 0.40 FLJ14109 fis, clone MAMMA1001322, moderately similar to B- CELL GROWTH FACTOR PRECURSOR. 203787_at single-stranded DNA SSBP2 Chr: 5q14.1 0.45 binding protein 2 210829_s_at single-stranded DNA SSBP2 Chr: 5q14.1 0.38 binding protein 2 210059_s_at mitogen-activated MAPK13 Chr: 6p21.31 0.46 protein kinase 13 231067_s_at A kinase (PRKA) AKAP12 Chr: 6q24-q25 0.55 anchor protein (gravin) 12 203819_s_at IGF-II mRNA-binding IMP-3 Chr: 7p11 0.13 protein 3 218640_s_at pleckstrin homology PLEKHF2 Chr: 8q22.1 0.35 domain containing, family F (with FYVE domain) member 2 222699_s_at pleckstrin homology PLEKHF2 Chr: 8q22.1 0.37 domain containing, family F (with FYVE domain) member 2 228284_at transducin-like TLE1 Chr: 9q21.32 0.50 enhancer of split 1 (E(sp1) homolog, Drosophila) 203222_s_at transducin-like TLE1 Chr: 9q21.32 0.39 enhancer of split 1 (E(sp1) homolog, Drosophila) 223398_at hypothetical protein MGC11115 Chr: 9q22.32 0.25 MGC11115 226809_at Homo sapiens cDNA — Cross Hyb Matching 0.17 FLJ30428 fis, clone Probes BRACE2008941.

TABLE 7 Differentially expressed probesets, which are able to discriminate on basis of loss of heterozygosity (LOH) on both the 1p and 19 q loci ratio loss/no Probe Set ID Title Gene Symbol Location loss 201177_s_at SUMO-1 activating enzyme UBA2 Chr: 19q12 0.45 subunit 2 215019_x_at KIAA1827 protein KIAA1827 Chr: 19q13 0.56 201258_at ribosomal protein S16 RPS16 Chr: 19q13.1 0.55 226131_s_at ribosomal protein S16 RPS16 Chr: 19q13.1 0.71 212131_at DKFZP434D1335 protein DKFZP434D1335 Chr: 19q13.12 0.49 218490_s_at zinc finger protein 302 ZNF302 Chr: 19q13.12 0.50 219818_s_at evolutionarily conserved G- ECGP Chr: 19q13.12 0.57 patch domain containing 231940_at KIAA1615 protein KIAA1615 Chr: 19q13.13 0.60 235648_at hypothetical protein MGC45586 Chr: 19q13.13 0.47 MGC45586 219495_s_at zinc finger protein 180 ZNF180 Chr: 19q13.2 0.55 (HHZ168) 206175_x_at zinc finger protein 222 ZNF222 Chr: 19q13.2 0.38 235702_at Homo sapiens transcribed — Chr: 19q13.31 0.59 sequences 205497_at zinc finger protein 175 ZNF175 Chr: 19q13.4 0.61 1556678_a_at Homo sapiens full length LOC284371 Chr: 19q13.41 0.58 insert cDNA clone ZD41C11 219848_s_at zinc finger protein 432 ZNF432 Chr: 19q13.41 0.51 228652_at hypothetical protein FLJ38288 Chr: 19q13.43 0.51 FLJ38288 242140_at similar to envelope protein LOC113386 Chr: 19q13.43 0.45 244740_at LOC342935 Chr: 19q13.43 0.61 208374_s_at capping protein (actin CAPZA1 Chr: 1p13.1 0.57 filament) muscle Z-line, alpha 1 211755_s_at ATP synthase, H+ ATP5F1 Chr: 1p13.2 0.61 transporting, mitochondrial F0 complex, subunit b, isoform 1 226000_at hypothetical protein DKFZp547A023 Chr: 1p13.2 0.48 DKFZp547A023 230300_at Homo sapiens transcribed — Chr: 1p13.3 0.49 sequences 222495_at protein x 013 AD-020 Chr: 1p13.3 0.52 223331_s_at DEAD (Asp-Glu-Ala-Asp) DDX20 Chr: 1p21.1-p13.2 0.54 box polypeptide 20 228661_s_at Homo sapiens, clone — Chr: 1p21.2 0.54 IMAGE: 4821863, mRNA 219939_s_at NRAS-related gene D1S155E Chr: 1p22 0.65 205263_at B-cell CLL/lymphoma 10 BCL10 Chr: 1p22 0.56 209187_at down-regulator of DR1 Chr: 1p22.1 0.50 transcription 1, TBP-binding (negative cofactor 2) 215017_s_at hypothetical protein FLJ20275 Chr: 1p22.1 0.24 FLJ20275 218462_at RNA processing factor 1 RPF1 Chr: 1p22.3 0.43 228135_at gm117 gm117 Chr: 1p22.3 0.57 200902_at 15 kDa selenoprotein 15-sep Chr: 1p31 0.56 202502_at acyl-Coenzyme A ACADM Chr: 1p31 0.51 dehydrogenase, C-4 to C-12 straight chain 212893_at DKFZP564I052 protein DKFZP564I052 Chr: 1p31.1 0.49 208709_s_at nardilysin (N-arginine NRD1 Chr: 1p32.2-p32.1 0.63 dibasic convertase) 223017_at endoplasmic reticulum TLP19 Chr: 1p32.3 0.51 thioredoxin superfamily member, 18 kDa 218080_x_at Fas (TNFRSF6) associated FAF1 Chr: 1p33 0.48 factor 1 242086_at spermatogenesis associated 6 SPATA6 Chr: 1p33 0.29 223230_at hypothetical protein FLJ14936 Chr: 1p33-p32.1 0.63 FLJ14936 213798_s_at CAP, adenylate cyclase- CAP1 Chr: 1p34.2 0.57 associated protein 1 (yeast) 228970_at archease ARCH Chr: 1p34.3 0.50 212491_s_at DnaJ (Hsp40) homolog, DNAJC8 Chr: 1p35.3 0.52 subfamily C, member 8 235058_at Homo sapiens transcribed — Chr: 1p36.11 0.62 sequence with weak similarity to protein ref: NP_060265.1 (H. sapiens) hypothetical protein FLJ20378 [Homo sapiens] 204299_at FUS interacting protein FUSIP1 Chr: 1p36.11 0.53 (serine-arginine rich) 1 206095_s_at FUS interacting protein FUSIP1 Chr: 1p36.11 0.51 (serine-arginine rich) 1 224867_at similar to Putative protein of Chr: 1p36.13 0.49 fungal and metazoan origin (11.1 kD) 202675_at succinate dehydrogenase SDHB Chr: 1p36.1-p35 0.68 complex, subunit B, iron sulfur (lp) 226532_at Full-length cDNA clone — Chr: 1p36.22 0.50 CS0DD009YD14 of Neuroblastoma Cot 50- normalized of Homo sapiens (human) 222000_at hypothetical protein LOC339448 Chr: 1p36.32 0.63 LOC339448 214611_at glutamate receptor, GRIK1 Chr: 21q22.11 0.39 ionotropic, kainate 1 203787_at single-stranded DNA binding SSBP2 Chr: 5q14.1 0.42 protein 2 231067_s_at A kinase (PRKA) anchor AKAP12 Chr: 6q24-q25 0.51 protein (gravin) 12 218640_s_at pleckstrin homology domain PLEKHF2 Chr: 8q22.1 0.26 containing, family F (with FYVE domain) member 2 222699_s_at pleckstrin homology domain PLEKHF2 Chr: 8q22.1 0.30 containing, family F (with FYVE domain) member 2 202241_at phosphoprotein regulated by C8FW Chr: 8q24.13 0.32 mitogenic pathways 223796_at cell recognition molecule CASPR3 Chr: 9p12 0.41 CASPR3 203222_s_at transducin-like enhancer of TLE1 Chr: 9q21.32 0.38 split 1 (E(sp1) homolog, Drosophila) 223398_at hypothetical protein MGC11115 Chr: 9q22.32 0.19 MGC11115 229498_at Homo sapiens transcribed MRNA; cDNA Chr: Xq26.2 0.26 sequences DKFZp779M2422 (from clone DKFZp779M2422) 226411_at similar to ecotropic viral LOC115704 Chr: 19p13.3 2.24 integration site 5; Neuroblastoma stage 4S gene 

1-21. (canceled)
 22. A method for producing a classification scheme for oligodendroglial tumors comprising the steps of: a) providing a plurality of reference samples, said reference samples comprising cell samples from a plurality of reference subjects suffering from oligodendroglial tumors, with known responsiveness to therapy and survival or with known loss of heterozygosity of 1p or 19q; b) providing reference profiles by establishing a gene expression profile, matched with parameters for treatment sensitivity, survival and loss of heterozygosity for each of said reference samples individually; c) clustering said individual reference profiles according to a statistical procedure, comprising: (i) K-means clustering, (ii) hierarchical clustering, and (iii) Pearson correlation coefficient analysis; and d) assigning an oligodendroglial tumor class according to treatment sensitivity, survival or loss of heterozygosity to each cluster.
 23. The method according to claim 22, wherein the clustering of said gene expression profiles is performed based on the information of differentially-expressed genes and the treatment sensitivity, survival or loss of heterozygosity of the subject.
 24. The method according to claim 22, wherein the clustering of said gene expression profiles with respect to treatment response is performed based on the information of the genes of Table
 3. 25. The method according to claim 22, wherein the clustering of said gene expression profiles with respect to survival is performed based on the information of the genes of Table
 4. 26. The method according to claim 22, wherein the clustering of said gene expression profiles with respect to loss of heterozygosity of 1p is performed based on the information of the genes of Table
 5. 27. The method according to claim 22, wherein the clustering of said gene expression profiles with respect to loss of heterozygosity of 19q is based on the information of the genes of Table
 6. 28. The method according to claim 22, wherein the clustering of said gene expression profiles with respect to loss of heterozygosity of 1p and 19q is performed based on the information of the genes of Table
 7. 29. A method for classifying an oligodendroglial tumor of a subject suffering from oligodendroglial tumor, comprising the steps of: a) providing a classification scheme for oligodendroglial tumors according to the method of claim 22; b) providing a subject profile by establishing a gene expression profile for said subject; c) clustering the subject profile together with a plurality of reference profiles; d) determining in said scheme the clustered position of said subject profile among the reference profiles; and e) assigning an oligodendroglial tumor class that corresponds to said clustered position to said oligodendroglial tumor.
 30. The method according to claim 29, wherein said gene expression profile with respect to treatment response comprises a plurality of expression parameters of a set of genes according to Table
 3. 31. The method according to claim 29, wherein said gene expression profile with respect to survival comprises a plurality of expression parameters of a set of genes according to Table
 4. 32. The method according to claim 29, wherein said gene expression profile with respect to 1p loss of heterozygosity comprises a plurality of expression parameters of a set of genes according to Table
 5. 33. The method according to claim 29, wherein said gene expression profile with respect to 19q heterozygosity comprises a plurality of expression parameters of a set of genes according to Table
 6. 34. The method according to claim 29, wherein said gene expression profile with respect to 1p and 19q loss of heterozygosity comprises a plurality of expression parameters of a set of genes according to Table
 7. 35. A method of determining the prognosis for a subject suffering from an oligodendroglial tumor, said method comprising the steps of: a) providing a classification scheme for oligodendroglial tumors by the method according to claim 22; b) determining a prognosis for each olidendroglial tumor class in said classification scheme based on clinical records for the subjects comprised in said class; c) establishing an oligodendroglial class of a subject suffering from an oligodendroglial tumor by classifying the oligodendroglial tumor in said subject according to the method of claim 29; and d) assigning to said subject the prognosis corresponding to the established oligodendroglial tumor class of said subject.
 36. A method of determining the prognosis for a subject suffering from an oligodendroglial tumor, said method comprising the steps of: a) isolating an RNA from tumor cells of said subject; b) preparing an antisense, biotinylated RNA to said RNA of step a); c) hybridizing said antisense to said RNA; d) normalizing a plurality of measured values for a gene set of Table 3; e) clustering the obtained data together with the reference data, obtained from a reference set of patient with known prognosis; and f) determining the prognosis on basis of the cluster to which the data of the subject are clustering.
 37. An oligonucleotide microarray of maximal 500 probesets, comprising at least 1 oligonucleotide probe capable of hybridizing under stringent conditions to a gene of an oligodendroglial tumor-associated genes selected from Tables 3-7.
 38. The oligonucleotide microarray of maximal 500 probesets of claim 37, wherein the probesets comprise at least 2 oligonucleotide probes.
 39. The oligonucleotide microarray of maximal 500 probesets of claim 37, wherein the probesets comprise at least 25 oligonucleotide probes.
 40. The oligonucleotide microarray of maximal 500 probesets of claim 37, wherein the probesets comprise at least 100 oligonucleotide probes.
 41. A kit comprising an oligonucleotide microarray according to claim 37 and means for comparing a gene expression profile determined by using said microarray with a database of oligodendroglial tumor reference expression profiles. 